Dissertations / Theses: 'Humanoid Robots'

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Che, Da. "Toward Humanoid Choreography and Dance." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1337187519.

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Nakhaei, Alireza. "Motion planning and perception : integration on humanoid robots." Thesis, Toulouse, INPT, 2009. http://www.theses.fr/2009INPT043H/document.

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Le chapitre 1 est pour l'essentiel une brève introduction générale qui donne le contexte générale de la planification et présente l'organisation du document dans son ensemble et quelques uns des points clés retenus : robot humanoïde, environnement non statique, perception par vision artificielle, et représentation de cet environnement par grilles d'occupation. Dans le chapitre 2, après une revue de littérature bien menée, l'auteur propose de considérer les points de repère de l'environnement dès la phase de planification de chemin afin de rendre plus robuste l'exécution des déplacements en cas d'évolution de l'environnement entre le moment où la planification est menée et celui où le robot se déplace ( évolution étant entendu comme liée à une amélioration de la connaissance par mise à jour, ou due à un changement de l'environnement lui-même). Le concept est décrit et une formalisation proposée. Le chapitre 3 s'intéresse en détail à la planification dans le cas d'environnements dynamiques. Les méthodes existantes, nombreuses, sont tout d'abord analysées et bien présentées. Le choix est fait ici de décrire l'environnement comme étant décomposé en cellules, regroupant elles-mêmes des voxels, éléments atomiques de la représentation. L'environnement étant changeant, l'auteur propose de réévaluer le plan préétabli à partir d'une bonne détection de la zone qui a pu se trouver modifiée dans l'environnement. L'approche est validée expérimentalement en utilisant une des plateformes robotiques du LAAS qui dispose de bonnes capacités de localisation : le manipulateur mobile Jido étant à ce jour plus performant sur ce plan que l'humanoïde HRP2, c'est lui qui a été utilisé. Ces expérimentations donnent des indications concordantes sur l'efficacité de l'approche retenue. Notons également que la planification s'appuie sur une boite englobante de l'humanoïde, et non pas sur une représentation plus riche (multi-degré-deliberté). En revanche, c'est bien de planification pour l'humanoïde considéré dans toute sa complexité qu'il s'agit au chapitre 4 : on s'intéresse ici à tous les degrés de liberté du robot. L'auteur propose des évolutions de méthodes existantes et en particulier sur la manière de tirer profit de la redondance cinématique. L'approche est bien décrite et permet d'inclure une phase d'optimisation de la posture globale du robot. Des exemples illustrent le propos et sont l'occasion de comparaison avec d'autres méthodes. Le chapitre 5 s'intéresse à la manière de modéliser l'environnement, sachant qu'on s'intéresse ici au cas d'une perception par vision artificielle, et précisément au cas de l'humanoïde, robot d'assurer lui-même cette perception au fur et à mesure de son avancée dans l'environnement. On est donc dans le cadre de la recherche de la meilleure vue suivante qui doit permettre d'enrichir au mieux la connaissance qu'a le robot de son environnement. L'approche retenue fait à nouveau appel à la boite englobante de l'humanoïde et non à sa représentation complète ; il sera intéressant de voir dans le futur ce que pourrait apporter la prise en compte des degrés de liberté de la tête ou du torse à la résolution de ce problème. Le chapitre 6 décrit la phase d'intégration de tous ces travaux sur la plateforme HRP2 du LAAS-CNRS, partie importante de tout travail de roboticien
This thesis starts by proposing a new framework for motion planning using stochastic maps, such as occupancy-grid maps. In autonomous robotics applications, the robot's map of the environment is typically constructed online, using techniques from SLAM. These methods can construct a dense map of the environment, or a sparse map that contains a set of identifiable landmarks. In this situation, path planning would be performed using the dense map, and the path would be executed in a sensor-based fashion, using feedback control to track the reference path based on sensor information regarding landmark position. Maximum-likelihood estimation techniques are used to model the sensing process as well as to estimate the most likely nominal path that will be followed by the robot during execution of the plan. The proposed approach is potentially a practical way to plan under the specific sorts of uncertainty confronted by a humanoid robot. The next chapter, presents methods for constructing free paths in dynamic environments. The chapter begins with a comprehensive review of past methods, ranging from modifying sampling-based methods for the dynamic obstacle problem, to methods that were specifically designed for this problem. The thesis proposes to adapt a method reported originally by Leven et al.. so that it can be used to plan paths for humanoid robots in dynamic environments. The basic idea of this method is to construct a mapping from voxels in a discretized representation of the workspace to vertices and arcs in a configuration space network built using sampling-based planning methods. When an obstacle intersects a voxel in the workspace, the corresponding nodes and arcs in the configuration space roadmap are marked as invalid. The part of the network that remains comprises the set of valid candidate paths. The specific approach described here extends previous work by imposing a two-level hierarchical structure on the representation of the workspace. The methods described in Chapters 2 and 3 essentially deal with low-dimensional problems (e.g., moving a bounding box). The reduction in dimensionality is essential, since the path planning problem confronted in these chapters is complicated by uncertainty and dynamic obstacles, respectively. Chapter 4 addresses the problem of planning the full motion of a humanoid robot (whole-body task planning). The approach presented here is essentially a four-step approach. First, multiple viable goal configurations are generated using a local task solver, and these are used in a classical path planning approach with one initial condition and multiple goals. This classical problem is solved using an RRT-based method. Once a path is found, optimization methods are applied to the goal posture. Finally, classic path optimization algorithms are applied to the solution path and posture optimization. The fifth chapter describes algorithms for building a representation of the environment using stereo vision as the sensing modality. Such algorithms are necessary components of the autonomous system proposed in the first chapter of the thesis. A simple occupancy-grid based method is proposed, in which each voxel in the grid is assigned a number indicating the probability that it is occupied. The representation is updated during execution based on values received from the sensing system. The sensor model used is a simple Gaussian observation model in which measured distance is assumed to be true distance plus additive Gaussian noise. Sequential Bayes updating is then used to incrementally update occupancy values as new measurements are received. Finally, chapter 6 provides some details about the overall system architecture, and in particular, about those components of the architecture that have been taken from existing software (and therefore, do not themselves represent contributions of the thesis). Several software systems are described, including GIK, WorldModelGrid3D, HppDynamicObstacle, and GenoM

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Sobrinho, Carlos Eduardo dos Reis Rodrigues. "Sensor fusion in humanoid robots." Master's thesis, Universidade de Aveiro, 2012. http://hdl.handle.net/10773/11052.

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Mestrado em Engenharia Electrónica e Telecomunicações
A fus~ao sensorial combina pe cas de informa c~ao proveniente de diferentes fontes/sensores de modo a obter informa c~ao global mais precisa quando comparada com sistemas que apenas dependem de fontes/sensores. Diferentes m etodos de fus~ao sensorial t^em sido desenvolvidos de forma a optimizar a resposta geral dos sistemas. Resultados nais, como a unidade inercial que funde duas fam lias diferentes de sensores para dar uma estimativa mais precisa/melhor dos dados sensoriais ou a auto-localiza c~ao do robot que deve ser capaz de avaliar a sua pr opria posi c~ao e consequentemente a posi c~ao dos membros da sua equipa s~ao exemplos da fus~ao sensorial. Esta tese ir a descrever detalhadamente, desde a fase de algoritmo at e a implementa c~ao juntamente com algumas bases matem aticas necess arias para a compreens~ao dos conceitos introduzidos, todo o trabalho desenvolvido para a equipa portuguesa que serviu para tornar o objectivo proposto em realidade: participar pela primeira vez na categoria Standard Platform League no RoboCup 2012.
The technology of sensor fusion combines pieces of information coming from di erent sources/sensors, resulting in an enhanced overall information accuracy when compared with systems that rely only on sources/sensors. Di erent sensor fusion methods have been developed in order to optimize the overall system output. End results like the inertial unit that fuses two di erent sensor families to give a more accurate/better estimate of the sensory data or the self-localization of the robot that should be able to evaluate its position and consequently its team members position. A walk-through, from the algorithm phase to the implementation, will be given in this thesis along with some mathematical background necessary to comprehend the concepts introduced and description of the auxiliary tools that were built for the Portuguese Team to help accomplish the objective: First presence in the Standard Platform League in the RoboCup 2012.

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Mendonça, José Lucas Lemos. "Behaviours for simulated humanoid robots." Master's thesis, Universidade de Aveiro, 2014. http://hdl.handle.net/10773/14699.

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Mestrado em Engenharia de Computadores e Telemática
This thesis in inserted in the FC Portugal 3D team, which competes in the humanoid simulation league 3D from RoboCup. The objectives of this thesis are to improve the behaviours already created and to develop tools to support the development and debugging of the robotic agent. With this in mind, the process of optimization was improved to make it more efficient and adapted to include the new heterogeneous models. Executing the optimization process, using the state of the art algorithm CMA-ES, the time of the getup was reduced by half. Afterwards, the agent was put running in sync mode, which allows the simulations to run as fast as the computer in use can process, and not the simulation speed of the competion with cycles of 20ms. In the agent posture, it is now used the information from the gyroscope and the euler angles are calculated to get a better estimative of the robot orientation. On the other hand, the agent architecture was updated and new behaviours were created and optimized to support the new heterogeneous models. In relation to the standard model, some behaviours execute faster because of their physical difference. In the slot behaviours, it is now possible to defined preconditions in each step, so the agent can abort the behaviour when any condition does not comply. This change reduces the time wasted executing all the behaviour in situations in which the success is improbable. In terms of tools, a Agent Monitor Window was created for each agent which can: present in runtime variables from the agent code; interact with the code trough widgets; and if the simulation is in sync mode, defined the simulation cycle time, with the possibility to pause it and execute step by step, which gives a great advantage in terms of analysing the agent execution. The second tool was a behaviour testes for behaviours defined in XML, which allows, in runtime, to change the behaviour to test, edit its content, aggregate different files in sequence and finally the tolls can execute various agents in parallel. The last tools is Log Analyser of the logs generated by the agents and the server, which allows: exporting in different formats, see in form of plots the variables parsed, filtrate the simulation information; and create a server simulation which can be used to analyse, in parallel, the plots of chosen variables and the simulation in a monitor.
Esta tese está inserida na equipa FC Portugal 3D, que compete na liga de futebol robótico simulado 3D. Os objetivos da tese são melhorar os comportamentos já existentes e desenvolver ferramentas de suporte ao desenvolvimento e depuração para o agente robótico. Nesse sentido, foi melhorado o processo de optimização de comportamentos de forma a torná-lo mais eficiente e adaptado para incluir os novos modelos heterogéneos disponibilizados. Ao executar o processo de optimização, usando o algoritmo de estado de arte CMA-ES, foi obtido reduções para metade do tempo nos comportamentos de levantar-se. Seguidamente o agente foi colocado a correr em modo síncrono, o que permite que as simulações corram à velocidade de processamento do computador em uso, e não à velocidade da simulação da competição em que cada ciclo demora 20ms. Assim é possível executar simulações e consequentemente inferir conclusões muito mais rapidamente. Passou-se a usar a informação de giroscópio e o cálculo dos ângulos de euler para obter uma melhor estimativa da rotação do robô. Por outro lado, devido ao lançamento de novos tipos de robôs, a arquitectura do agente teve de ser atualizada e novos comportamentos foram criados e optimizados para estes novos modelos. Em relação ao modelo original, alguns comportamentos são executados mais rapidamente e melhor pelos modelos novos, devido às suas alterações físicas. Por fim, nos comportamentos foi dada a possibilidade de definir pré condições em etapa do mesmo, para que possa ser abortado caso as condições não se verifiquem. Esta alteração veio reduzir o tempo desperdiçado a executar a totalidade do comportamento em situações em que não é provável o seu sucesso . Em termos de ferramentas, foi colocada uma Janela de Monitor de Agente para cada agente que, apresenta em tempo de simulação variáveis que o código do agente disponibiliza, interage com código através de widgets de seleção ou preenchimento, e se a simulação estiver a correr em modo síncrono, permite definir o tempo de ciclo da simulação, pausá-la e executar ciclo a ciclo, o que permite vantagens óbvias em termos de análise de execução dos agentes. Seguidamente, foi criada uma ferramenta de teste para comportamentos definidos em XML, que permite, em tempo de execução, alterar o ficheiro a testar, alterar o seu conteúdo, agrupar vários ficheiros em sequências e executar vários agentes em paralelo. Por fim, a última ferramenta é um Analizador de Logs gerados pelos agentes e pelo simulador que permite, entre outras funcionalidades, ver em forma de gráficos variáveis da simulação, exportar para diferentes formatos, filtrar a simulação usando informação da mesma e correr um servidor de forma a ser possível analizar em paralelo, gráficos de variáveis escolhidas e a simulação num visualizador.

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Tay, Junyun. "Autonomous Animation of Humanoid Robots." Research Showcase @ CMU, 2016. http://repository.cmu.edu/dissertations/838.

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Gestures and other body movements of humanoid robots can be used to convey meanings which are extracted from an input signal, such as speech or music. For example, the humanoid robot waves its arm to say goodbye or nods its head to dance to the beats of the music. This thesis investigates how to autonomously animate a real humanoid robot given an input signal. This thesis addresses five core challenges, namely: Representation of motions, Mappings between meanings and motions, Selection of relevant motions, Synchronization of motion sequences to the input signal, and Stability of the motion sequences (R-M-S3). We define parameterized motions that allow a large variation of whole body motions to be generated from a small core motion library and synchronization of the motions to different input signals. To assign meanings to motions, we represent meanings using labels and map motions to labels autonomously using motion features. We also examine different metrics to determine similar motions so that a new motion is mapped to existing labels of the most similar motion. We explain how we select relevant motions using labels, synchronize the motion sequence to the input signal, and consider the audience’s preferences. We contribute an algorithm that determines the stability of a motion sequence. We also define the term relative stability, where the stability of one motion sequence is compared to other motion sequences. We contribute an algorithm to determine the most stable motion sequence so that the humanoid robot animates continuously without interruptions. We demonstrate our work with two input signals – music and speech, where a humanoid robot autonomously dances to any piece of music using the beats and emotions of the music and also autonomously gestures according to its speech. We describe how we use our solutions to R-M-S3, and present a complete algorithm that captures the meanings of the input signal and weighs the selection of the best sequence using two criteria: audience feedback and stability. Our approach and algorithms are general to autonomously animate humanoid robots, and we use a real NAO humanoid robot and in simulation as an example.

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Seepanomwan, Kristsana. "Mental imagery in humanoid robots." Thesis, University of Plymouth, 2016. http://hdl.handle.net/10026.1/4581.

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Mental imagery presents humans with the opportunity to predict prospective happenings based on own intended actions, to reminisce occurrences from the past and reproduce the perceptual experience. This cognitive capability is mandatory for human survival in this folding and changing world. By means of internal representation, mental imagery offers other cognitive functions (e.g., decision making, planning) the possibility to assess information on objects or events that are not being perceived. Furthermore, there is evidence to suggest that humans are able to employ this ability in the early stages of infancy. Although materialisation of humanoid robot employment in the future appears to be promising, comprehensive research on mental imagery in these robots is lacking. Working within a human environment required more than a set of pre-programmed actions. This thesis aims to investigate the use of mental imagery in humanoid robots, which could be used to serve the demands of their cognitive skills as in humans. Based on empirical data and neuro-imaging studies on mental imagery, the thesis proposes a novel neurorobotic framework which proposes to facilitate humanoid robots to exploit mental imagery. Through conduction of a series of experiments on mental rotation and tool use, the results from this study confirm this potential. Chapters 5 and 6 detail experiments on mental rotation that investigate a bio-constrained neural network framework accounting for mental rotation processes. They are based on neural mechanisms involving not only visual imagery, but also affordance encoding, motor simulation, and the anticipation of the visual consequences of actions. The proposed model is in agreement with the theoretical and empirical research on mental rotation. The models were validated with both a simulated and physical humanoid robot (iCub), engaged in solving a typical mental rotation task. The results show that the model is able to solve a typical mental rotation task and in agreement with data from psychology experiments, they also show response times linearly dependent on the angular disparity between the objects. Furthermore, the experiments in chapter 6 propose a novel neurorobotic model that has a macro-architecture constrained by knowledge on brain, which encompasses a rather general mental rotation mechanism and incorporates a biologically plausible decision making mechanism. The new model is tested within the humanoid robot iCub in tasks requiring to mentally rotate 2D geometrical images appearing on a computer screen. The results show that the robot has an enhanced capacity to generalize mental rotation of new objects and shows the possible effects of overt movements of the wrist on mental rotation. These results indicate that the model represents a further step in the identification of the embodied neural mechanisms that might underlie mental rotation in humans and might also give hints to enhance robots' planning capabilities. In Chapter 7, the primary purpose for conducting the experiment on tool use development through computational modelling refers to the demonstration that developmental characteristics of tool use identified in human infants can be attributed to intrinsic motivations. Through the processes of sensorimotor learning and rewarding mechanisms, intrinsic motivations play a key role as a driving force that drives infants to exhibit exploratory behaviours, i.e., play. Sensorimotor learning permits an emergence of other cognitive functions, i.e., affordances, mental imagery and problem-solving. Two hypotheses on tool use development are also conducted thoroughly. Secondly, the experiment tests two candidate mechanisms that might underlie an ability to use a tool in infants: overt movements and mental imagery. By means of reinforcement learning and sensorimotor learning, knowledge of how to use a tool might emerge through random movements or trial-and-error which might reveal a solution (sequence of actions) of solving a given tool use task accidentally. On the other hand, mental imagery was used to replace the outcome of overt movements in the processes of self-determined rewards. Instead of determining a reward from physical interactions, mental imagery allows the robots to evaluate a consequence of actions, in mind, before performing movements to solve a given tool use task. Therefore, collectively, the case of mental imagery in humanoid robots was systematically addressed by means of a number of neurorobotic models and, furthermore, two categories of spatial problem solving tasks: mental rotation and tool use. Mental rotation evidently involves the employment of mental imagery and this thesis confirms the potential for its exploitation by humanoid robots. Additionally, the studies on tool use demonstrate that the key components assumed and included in the experiments on mental rotation, namely affordances and mental imagery, can be acquired by robots through the processes of sensorimotor learning.

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Pretto, Alberto. "Visual-SLAM for Humanoid Robots." Doctoral thesis, Università degli studi di Padova, 2009. http://hdl.handle.net/11577/3426516.

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In robotics the Simultaneous Localization and Mapping (SLAM) is the problem in which an autonomous robots acquires a map of the surrounding environment while at the same time localizes itself inside this map. In the last years a lot of researchers have spent a great eﬀort in developing new families of algorithms, using several sensors and robotic platforms. One of the most challenging ﬁeld of research in SLAM is the so called Visual-SLAM problem, in which various types of cameras are used as sensor for the navigation. Cameras are inexpensive sensors and can provide rich information about the surrounding environment, on the other hand the complexity of the computer vision tasks and the strong dependence on the characteristics of the environment in current approaches makes the Visual-SLAM far to be considered a closed problem. Most of the SLAM algorithm are usually tested on wheeled robot. These platforms have become robust and stable, on the other hand the research in robot design moves toward a new family of robot platforms, the humanoid robots. Just like humans, a humanoid robot can adapt itself to changes in the environment in order to eﬃciently reach its goals. Despite that, only a few roboticists focused theirs research on stable implementation of SLAM and Visual SLAM algorithms well suited for humanoid robots. Humanoid platforms raise issues which can compromise the stability of the conventional navigation algorithms, especially for vision-based approaches. A humanoid robot can move in 3D without the usual planar motion assumption that constraint the movement in 2D, usually with quick and complex movements combined with unpredictable vibrations, compromising the reliability of the acquired sensors data, for example introducing in the images grabbed by the camera an undesired motion blur eﬀect. Due to the strong balance constraints, a humanoid robot usually can’t be equipped with powerfull but hefty computer boards: this limits the implementation of complex and computational expensive algorithms. Moreover, unlike wheeled robots, its complex kinematics usually forbids a reliable reconstruction of the motion from the servo-motor encoders. In this thesis, we focus on studying and developing new techniques addressing the Visual-SLAM problem, with particular attention to the issues related to using as experimental platform small humanoid robots equipped with a single perspective camera. The main eﬀorts in SLAM and Visual SLAM research areas have been put into the estimation functionality. However, most of the functionalities involved in Visual SLAM are in perception processes. In this thesis we therefore focus on the improvement of the perceptual processes, from a computer vision point-of-view. We faced small humanoid robot related issues like low-computational capability, the low quality of the sensor data and the high degrees of freedom of the motion. We cope with the low computational resources presenting a new similarity measure for images based on a compact signature to be used in image-based topological SLAM problem. The motion blur problem is faced proposing a new feature detection and tracking scheme that is robust even to non-uniform motion blur. We develop a framework for visual odometry based on features robust to motion blur. We ﬁnally propose an homography-based approach to 3D visual SLAM, using the information provided by a single camera mounted on a humanoid robot, based on the assumption that the robot moves on a planar environment. All proposed methods have been validated with experiments and comparative validation using both standard datasets and images taken by the cameras mounted on walking small humanoid robots.
Nell’ambito della robotica, il Simultaneous Localization and Mapping (SLAM) é il processo grazie al quale un robot autonomo é in grado di creare una mappa dell’ambiente circostante e allo stesso tempo di localizzarsi avvalendosi di tale mappa. Negli ultimi anni un considerevole numero di ricercatori ha sviluppato nuove famiglie di algoritmi di SLAM, basati su vari sensori e utilizzando varie piattaforme robotiche. Uno degli ambiti più complessi nella ricerca sullo SLAM é il cosiddetto Visual-SLAM, che prevede l’utilizzo di vari tipi di telecamera come sensore per la navigazione. Le telecamere sono sensori economici che raccolgono molte informazioni sull’ambiente circostante. D’altro canto, la complessità degli algoritmi di visione artiﬁciale e la forte dipendenza degli approcci attualmente realizzati dalle caratteristiche dell’ambiente, rendono il Visual-SLAM un problema lontano dal poter essere considerato risolto. Molti degli algoritmi di SLAM sono solitamente testati usando robot dotati di ruote. Sebbene tali piattaforme siano ormai robuste e stabili, la ricerca sulla progettazione di nuove piattaforme robotiche sta in parte migrando verso la robotica umanoide. Proprio come gli esseri umani, i robot umanoidi sono in grado di adattarsi ai cambiamenti dell’ambiente per raggiungere eﬃcacemente i propri obiettivi. Nonostante ciò, solo pochi ricercatori hanno focalizzato i loro sforzi su implementazioni stabili di algoritmi di SLAM e Visual-SLAM adatti ai robot umanoidi. Tali piattaforme robotiche introducono nuove problematiche che possono compromettere la stabilità degli algoritmi di navigazione convenzionali, specie se basati sulla visione. I robot umanoidi sono dotati di un alto grado di libertà di movimento, con la possibilità di eﬀettuare velocemente movimenti complessi: tali caratteristiche introducono negli spostamenti vibrazioni non deterministiche in grado di compromettere l’aﬃdabilit` dei dati sensoriali acquisiti, per esempio introducendo nei ﬂussi video eﬀetti indesiderati quali il motion blur. A causa dei vincoli imposti dal bilanciamento del corpo, inoltre, tali robot non sempre possono essere dotati di unit` di elaborazione molto performanti che spesso sono ingombranti e dal peso elevato: ci` limita l’utilizzo di algoritmi complessi e computazionalmente gravosi. Inﬁne, al contrario di quanto accade per i robot dotati di ruote, la complessa cinematica di un robot umanoide impedisce di ricostruire il movimento basandosi sulle informazioni provenienti dagli encoder posti sui motori. In questa tesi ci si é focalizzati sullo studio e sullo sviluppo di nuove metodologie per aﬀrontare il problema del Visual-SLAM, ponendo particolare enfasi ai problemi legati all’utilizzo di piccoli robot umanoidi dotati di una singola telecamera come piattaforme per gli esperimenti. I maggiori sforzi nell’ambito della ricerca sullo SLAM e sul Visual-SLAM si sono concentrati nel campo del processo di stima dello stato del robot, ad esempio la stima della propria posizione e della mappa dell’ambiente. D’altra parte, la maggior parte delle problematiche incontrate nella ricerca sul Visual-SLAM sono legate al processo di percezione, ovvero all’interpretazione dei dati provenienti dai sensori. In questa tesi ci si é perciò concentrati sul miglioramento dei processi percettivi da un punto di vista della visione artiﬁciale. Sono stati aﬀrontati i problemi che scaturiscono dall’utilizzo di piccoli robot umanoidi come piattaforme sperimentali, come ad esempio la bassa capacità di calcolo, la bassa qualit` dei dati sensoriali e l’elevato numero di gradi di libertà nei movimenti. La bassa capacità di calcolo ha portato alla creazione di un nuovo metodo per misurare la similarità tra le immagini, che fa uso di una descrizione dell’immagine compatta, utilizzabile in applicazioni di SLAM topologico. Il problema del motion blur é stato aﬀrontato proponendo una nuova tecnica di rilevamento di feature visive, unitamente ad un nuovo schema di tracking, robusto an- che in caso di motion blur non uniforme. E’ stato altresì sviluppato un framework per l’odometria basata sulle immagini, che fa uso delle feature visive presentate. Si propone inﬁne un approccio al Visual-SLAM basato sulle omograﬁe, che sfrutta le informazioni ottenute da una singola telecamera montata su un robot umanoide. Tale approccio si basa sull’assunzione che il robot si muove su una superﬁcie piana. Tutti i metodi proposti sono stati validati con esperimenti e studi comparativi, usando sia dataset standard che immagini acquisite dalle telecamere installate su piccoli robot umanoidi.

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Alkhulayfi, Khalid Abdullah. "Vision-Based Motion for a Humanoid Robot." PDXScholar, 2016. https://pdxscholar.library.pdx.edu/open_access_etds/3176.

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The overall objective of this thesis is to build an integrated, inexpensive, human-sized humanoid robot from scratch that looks and behaves like a human. More specifically, my goal is to build an android robot called Marie Curie robot that can act like a human actor in the Portland Cyber Theater in the play Quantum Debate with a known script of every robot behavior. In order to achieve this goal, the humanoid robot need to has degrees of freedom (DOF) similar to human DOFs. Each part of the Curie robot was built to achieve the goal of building a complete humanoid robot. The important additional constraints of this project were: 1) to build the robot from available components, 2) to minimize costs, and 3) to be simple enough that the design can be replicated by non-experts, so they can create robot theaters worldwide. Furthermore, the robot appears lifelike because it executes two main behaviors like a human being. The first behavior is tracking where the humanoid robot uses a tracking algorithm to follow a human being. In other words, the tracking algorithm allows the robot to control its neck using the information taken from the vision system to look at the nearest human face. In addition, the robot uses the same vision system to track labeled objects. The second behavior is grasping where the inverse kinematics (IK) is calculated so the robot can move its hand to a specific coordinate in the surrounding space. IK gives the robot the ability to move its end-effector (hand) closer to how humans move their hands.

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Pajon, Adrien. "Humanoid robots walking with soft soles." Thesis, Montpellier, 2017. http://www.theses.fr/2017MONTS060/document.

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Lorsque des changements inattendus de la surface du sol se produisent lors de la marche, le système nerveux central humain doit appliquer des mesures de contrôle appropriées pour assurer une stabilité dynamique. De nombreuses études dans le domaine de la commande moteur ont étudié les mécanismes d'un tel contrôle postural et ont largement décrit comment les trajectoires du centre de masse (COM), le placement des pas et l'activité musculaire s'adaptent pour éviter une perte d'équilibre. Les mesures que nous avons effectuées montrent qu'en arrivant sur un sol mou, les participants ont modulé de façon active les forces de réaction au sol (GRF) sous le pied de support afin d'exploiter les propriétés élastiques et déformables de la surface pour amortir l'impact et probablement dissiper l'énergie mécanique accumulée pendant la ‘chute’ sur la nouvelle surface déformable. Afin de contrôler plus efficacement l'interaction pieds-sol des robots humanoïdes pendant la marche, nous proposons d'ajouter des semelles extérieures souples (c'est-à-dire déformables) aux pieds. Elles absorbent les impacts et limitent les effets des irrégularités du sol pendant le mouvement sur des terrains accidentés. Cependant, ils introduisent des degrés de liberté passifs (déformations sous les pieds) qui complexifient les tâches d'estimation de l'état du robot et ainsi que sa stabilisation globale. Pour résoudre ce problème, nous avons conçu un nouveau générateur de modèle de marche (WPG) basé sur une minimisation de la consommation d'énergie qui génère les paramètres nécessaires pour utiliser conjointement un estimateur de déformation basé sur un modèle éléments finis (FEM) de la semelle souple pour prendre en compte sa déformation lors du mouvement. Un tel modèle FEM est coûteux en temps de calcul et empêche la réactivité en ligne. Par conséquent, nous avons développé une boucle de contrôle qui stabilise les robots humanoïdes lors de la marche avec des semelles souples sur terrain plat et irrégulier. Notre contrôleur en boucle fermée minimise les erreurs sur le centre de masse (COM) et le point de moment nul (ZMP) avec un contrôle en admittance des pieds basé sur un estimateur de déformation simplifié. Nous démontrons son efficacité expérimentalement en faisant marcher le robot humanoïde HRP-4 sur des graviers
When unexpected changes of the ground surface occur while walking, the human central nervous system needs to apply appropriate control actions to assure dynamic stability. Many studies in the motor control field have investigated the mechanisms of such a postural control and have widely described how center of mass (COM) trajectories, step patterns and muscle activity adapt to avoid loss of balance. Measurements we conducted show that when stepping over a soft ground, participants actively modulated the ground reaction forces (GRF) under the supporting foot in order to exploit the elastic and compliant properties of the surface to dampen the impact and to likely dissipate the mechanical energy accumulated during the ‘fall’ onto the new compliant surface.In order to control more efficiently the feet-ground interaction of humanoid robots during walking, we propose adding outer soft (i.e. compliant) soles to the feet. They absorb impacts and cast ground unevenness during locomotion on rough terrains. However, they introduce passive degrees of freedom (deformations under the feet) that complexify the tasks of state estimation and overall robot stabilization. To address this problem, we devised a new walking pattern generator (WPG) based on a minimization of the energy consumption that offers the necessary parameters to be used jointly with a sole deformation estimator based on finite element model (FEM) of the soft sole to take into account the sole deformation during the motion. Such FEM computation is time costly and inhibit online reactivity. Hence, we developed a control loop that stabilizes humanoid robots when walking with soft soles on flat and uneven terrain. Our closed-loop controller minimizes the errors on the center of mass (COM) and the zero-moment point (ZMP) with an admittance control of the feet based on a simple deformation estimator. We demonstrate its effectiveness in real experiments on the HRP-4 humanoid walking on gravels

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Kim, Hyun-Don. "Binaural Active Audition for Humanoid Robots." 京都大学 (Kyoto University), 2008. http://hdl.handle.net/2433/123821.

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Balland, Olivier. "Collaborative motion planning of humanoid robots." Thesis, KTH, Reglerteknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-148115.

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For a matter of efficiency and robustness, it is often better to use a team of robots instead of a single agent to solve a given problem. A key challenge with multi-robot systems is the collaboration in order to accomplish complex tasks. To coordinate them, we can pre-compute their behavior. However, this method might not be robust to some events such as modification of environment or robots team. To overcome this issue, an adaptive decentralized coordination framework is needed for heterogeneous multiple robot systems. We consider a team of two robots NAOs which can only exchange information when they are close to each other, or via symbols grounded to each embodiment. They are initially in a room a few meters away from each other. The goal is to make them meet and then perform an action such as exchanging an object or some information. In this thesis, we study first robots specifications and adopt tools used for robot control. A tracking method in a simple situation is then described. The robots’ strategy is structured and improved adding obstacles limiting the two agents’ motion. The achieved robust framework allows two humanoid robots to meet, even if one has a problem and can not move.

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Nortman, Scott D. "Design, construction, and control of an autonomous humanoid robot." [Gainesville, Fla.] : University of Florida, 2002. http://purl.fcla.edu/fcla/etd/UFE1000147.

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Thesis (M.S.)--University of Florida, 2002.
Title from title page of source document. Document formatted into pages; contains vii, 68 p.; also contains graphics. Includes vita. Includes bibliographical references.

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Patacchiola, Massimiliano. "A developmental model of trust in humanoid robots." Thesis, University of Plymouth, 2018. http://hdl.handle.net/10026.1/12828.

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Trust between humans and artificial systems has recently received increased attention due to the widespread use of autonomous systems in our society. In this context trust plays a dual role. On the one hand it is necessary to build robots that are perceived as trustworthy by humans. On the other hand we need to give to those robots the ability to discriminate between reliable and unreliable informants. This thesis focused on the second problem, presenting an interdisciplinary investigation of trust, in particular a computational model based on neuroscientific and psychological assumptions. First of all, the use of Bayesian networks for modelling causal relationships was investigated. This approach follows the well known theory-theory framework of the Theory of Mind (ToM) and an established line of research based on the Bayesian description of mental processes. Next, the role of gaze in human-robot interaction has been investigated. The results of this research were used to design a head pose estimation system based on Convolutional Neural Networks. The system can be used in robotic platforms to facilitate joint attention tasks and enhance trust. Finally, everything was integrated into a structured cognitive architecture. The architecture is based on an actor-critic reinforcement learning framework and an intrinsic motivation feedback given by a Bayesian network. In order to evaluate the model, the architecture was embodied in the iCub humanoid robot and used to replicate a developmental experiment. The model provides a plausible description of children's reasoning that sheds some light on the underlying mechanism involved in trust-based learning. In the last part of the thesis the contribution of human-robot interaction research is discussed, with the aim of understanding the factors that influence the establishment of trust during joint tasks. Overall, this thesis provides a computational model of trust that takes into account the development of cognitive abilities in children, with a particular emphasis on the ToM and the underlying neural dynamics.

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Griffin, Robert James. "Natural, Efficient Walking for Compliant Humanoid Robots." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/79964.

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Bipedal robots offer a uniquely flexible platform capable of navigating complex, human-centric environments. This makes them ideally suited for a variety of missions, including disaster response and relief, emergency scenarios, or exoskeleton systems for individuals with disabilities. This, however, requires significant advances in humanoid locomotion and control, as they are still slow, unnatural, inefficient, and relatively unstable. The work of this dissertation the state of the art with the aim was of increasing the robustness and efficiency of these bipedal walking platforms. We present a series of control improvements to enable reliable, robust, natural bipedal locomotion that was validated on a variety of bipedal robots using both hardware and simulation experiments. A huge part of reliable walking involves maximizing the robot's control authority. We first present the development of a model predictive controller to both control the ground reaction forces and perform step adjustment for walking stabilization using a mixed-integer quadratic program. This represents the first model predictive controller to include step rotation in the optimization and leverage the capabilities of the time-varying divergent component of motion for navigating rough terrain. We also analyze the potential capabilities of model predictive controllers for the control of bipedal walking. As an alternative to standard trajectory optimization-based model predictive controls, we present several optimization-based control schemes that leverage more traditional bipedal walking control approaches by embedding a proportional feedback controller into a quadratic program. This controller is capable of combining multiple feedback mechanisms: ground reaction feedback (the "ankle strategy"), angular momentum (the "hip strategy"), swing foot speed up, and step adjustment. This allows the robot to effectively shift its weight, pitch its torso, and adjust its feet to retain balance, while considering environmental constraints, when available. To enable the robot to walk with straightened legs, we present a strategy that insures that the dynamic plans are kinematically and dynamically feasible to execute using straight legs. The effects of timing on dynamic plans are typically ignored, resulting in them potentially requiring significantly bending the legs during execution. This algorithm modifies the step timings to insure the plan can be executed without bending the legs beyond certain angle, while leaving the desired footsteps unmodified. To then achieve walking with straight legs we then presented a novel approach for indirectly controlling the center of mass height through the leg angles. This avoids complicated height planning techniques that are both computationally expensive and often not general enough to consider variable terrain by effectively biasing the solution of the whole-body controller towards using straighter legs. To incorporate the toe-off motion that is essential to both natural and straight leg walking, we also present a strategy for toe-off control that allows it to be an emergent behavior of the whole-body controller. The proposed approach was demonstrated through a series of simulation and experimental results on a variety of platforms. Model predictive control for step adjustment and rough terrain is illustrated in simulation, while the other step adjustment strategies and straight leg walking approaches are presented recovering from external disturbances and walking over a variety of terrains in hardware experiments. We discuss many of the practical considerations and limitations required when porting simulation-based controller development to hardware platforms. Using the presented approaches, we also demonstrated a important concept: using whole-body control frameworks, not every desired motion need be directly commanded. Many of these motions, such as toe-off, may simply be emergent behaviors that result by attempting to satisfy other objectives, such as desired reaction forces. We also showed that optimization is a very powerful tool for walking control, able to determine both stabilizing inputs and joint torques.
Ph. D.

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Clercq, Charles. "Implementation of neuromorphic vision solutions for humanoid robots." Paris 6, 2013. http://www.theses.fr/2013PA066072.

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L'objectif de cette these était le développement d'un système visuel bio-inspiré dit «neuromorphique », pouvant s'intégrer au sein du robot humanoïde « iCub », et ce afin d'en accroître l'autonomie notamment en navigation. Afin de bien comprendre le fonctionnement du paradigme « event-based » , la stratégie utilisée tant du point de vue de l'extraction que de la transmission de l'information est premièrement détaillée. Ensuite, les contributions méthodologiques de mes travaux sur l'exploitation d'une telle information y sont décrites : je me suis particulièrement intéressé au calcul du flot optique. J'ai développé des méthodologies, dérivées de ce calcul, permettant de déterminer des informations cruciales pour la navigation robotique telles le « foyer d'expansion » et le « temps avant impact ». Toutes ces méthodes sont validées sur des données réelles, et avec, dans le cas du « foyer d'expansion », l'utilisation conjointe de données simulées
Artificial vision aims to confer to machines the ability to perceive and to interpret their environment by inspiring from the biological vision. Since the beginning of image processing and machine vision fields in the 60's, numerous techniques have been developed to extract and to process visual information in an all implicitly accepted and unique context of frames. This is shown to be in contradiction with biologic eyes which have discarded through evolution mechanisms the concepts of frame and synchronized pixels. This thesis aims to switch the classic computer vision paradigm based on frame for the biological one. New vision algorithms are developed using this new paradigm for the iCub humanoid robot, in the context of the european project eMorph. The aimed goal is to design a neuro-inspired vision based navigation ability to the robot. This neuro-inspired vision is expected to be much more accurate and energy efficient

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Stasse, Olivier. "Vision based motion generation for humanoid robots." Habilitation à diriger des recherches, Université Paul Sabatier - Toulouse III, 2013. http://tel.archives-ouvertes.fr/tel-00843953.

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Ce manuscrit présente mes activités de recherche sur les comportements basés vision pour des robots complexes comme les robots humanoïdes. La question scientifique sous-jacente qui structure ce travail est la suivante: " Quels sont les processus de décisions qui permettent à un robot humanoïde de générer des mouvements en temps réel basés sur des informations visuelles ?" Au football, les êtres humains peuvent décider de frapper une balle alors qu'ils courent et que tous les autres joueurs sont constamment en train de bouger. Reformuler comme un problème d'optimisation pour un robot humanoïde, trouver une solution pour un tel comportement est généralement très difficile du point de vue calculatoire. Par exemple, le problème de la recherche visuelle a été démontré comme étant NP-complet. La première partie de ce travail concerne la génération de mouvements temps réel. Partant des contraintes générales qu'un robot humanoïde doit remplir pour générer un mouvement faisable, des problèmes fondamentaux sont présentés. A partir de ceux-ci, plusieurs contributions permettant à un robot humanoïde de réagira à des changements de l'environnement sont présentés. Ils concernent la génération de la marche, les mouvements corps complets pour éviter des obstacles, et la planification de pas en temps réel dans des environnements contraints. La deuxième partie de ce travail concerne l'acquisition temps-réel de connaissance sur l'environnement à partir de la vision par ordinateur. Deux comportements principaux sont considérés: la recherche visuelle et la construction d'un modèle visuel d'un objet. Ils sont considérés tout en prenant compte le modèle du capteur, le coût du mouvement, les contraintes mécaniques du robot, la géométrie de l'environnement ainsi que les limitations du processus de vision. De plus des contributions sur le couplage de l'auto-localisation basé cartes avec la marche, la génération de pas basé sur l'asservissement visuel seront présentés. Finalement les technologies centrales développées dans les contextes précédents ont été utilisées dans différentes applications: l'interaction homme-robot, la téléopération, l'analyse de mouvement humains. Basé sur le retour d'expérience de plusieurs démonstrateurs intégrés sur le robot humanoïde HRP-2, la dernière partie de cette thèse proposent des pistes pour des idées permettant de lever les verrous technologiques actuels de la robotique humanoïde.

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Rucinski, Marek. "Modelling learning to count in humanoid robots." Thesis, University of Plymouth, 2014. http://hdl.handle.net/10026.1/2995.

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This thesis concerns the formulation of novel developmental robotics models of embodied phenomena in number learning. Learning to count is believed to be of paramount importance for the acquisition of the remarkable fluency with which humans are able to manipulate numbers and other abstract concepts derived from them later in life. The ever-increasing amount of evidence for the embodied nature of human mathematical thinking suggests that the investigation of numerical cognition with the use of robotic cognitive models has a high potential of contributing toward the better understanding of the involved mechanisms. This thesis focuses on two particular groups of embodied effects tightly linked with learning to count. The first considered phenomenon is the contribution of the counting gestures to the counting accuracy of young children during the period of their acquisition of the skill. The second phenomenon, which arises over a longer time scale, is the human tendency to internally associate numbers with space that results, among others, in the widely-studied SNARC effect. The PhD research contributes to the knowledge in the subject by formulating novel neuro-robotic cognitive models of these phenomena, and by employing these in two series of simulation experiments. In the context of the counting gestures the simulations provide evidence for the importance of learning the number words prior to learning to count, for the usefulness of the proprioceptive information connected with gestures to improving counting accuracy, and for the significance of the spatial correspondence between the indicative acts and the objects being enumerated. In the context of the model of spatial-numerical associations the simulations demonstrate for the first time that these may arise as a consequence of the consistent spatial biases present when children are learning to count. Finally, based on the experience gathered throughout both modelling experiments, specific guidelines concerning future efforts in the application of robotic modelling in mathematical cognition are formulated.

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Tikhanoff, Vadim. "Development of cognitive capabilities in humanoid robots." Thesis, University of Plymouth, 2009. http://hdl.handle.net/10026.1/2807.

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Building intelligent systems with human level of competence is the ultimate grand challenge for science and technology in general, and especially for the computational intelligence community. Recent theories in autonomous cognitive systems have focused on the close integration (grounding) of communication with perception, categorisation and action. Cognitive systems are essential for integrated multi-platform systems that are capable of sensing and communicating. This thesis presents a cognitive system for a humanoid robot that integrates abilities such as object detection and recognition, which are merged with natural language understanding and refined motor controls. The work includes three studies; (1) the use of generic manipulation of objects using the NMFT algorithm, by successfully testing the extension of the NMFT to control robot behaviour; (2) a study of the development of a robotic simulator; (3) robotic simulation experiments showing that a humanoid robot is able to acquire complex behavioural, cognitive, and linguistic skills through individual and social learning. The robot is able to learn to handle and manipulate objects autonomously, to cooperate with human users, and to adapt its abilities to changes in internal and environmental conditions. The model and the experimental results reported in this thesis, emphasise the importance of embodied cognition, i.e. the humanoid robot's physical interaction between its body and the environment.

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Muecke, Karl James. "An Analytical Motion Filter for Humanoid Robots." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/26686.

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Mimicking human motion with a humanoid robot can prove to be useful for studying gaits, designing better prostheses, or assisting the elderly or disabled. Directly mimicking and implementing a motion of a human on a humanoid robot may not be successful because of the different dynamic characteristics between them, which may cause the robot to fall down due to instability. Using the Zero Moment Point as the stability criteria, this work proposes an Analytical Motion Filter (AMF), which stabilizes a reference motion that can come from human motion capture data, gait synthesis using kinematics, or animation software, while satisfying common constraints. In order to determine how the AMF stabilized a motion, the different kinds of instabilities were identified and classified when examining the reference motions. The different cases of instability gave more insight as to why a particular motion was unstable: the motion was too fast, too slow, or inherently unstable. In order to stabilize the gait two primary methods were utilized: time and spatial scaling. Spatial scaling scaled the COM trajectory down towards a known stable trajectory. Time scaling worked similarly by changing the speed of the motion, but was limited in effectiveness based on the types of instabilities in the motion and the coupling of the spatial directions. Other constraints applied to the AMF and combinations of the different methods produced interesting results that gave more insight into the stability of the gait. The AMF was tested using both simulations and physical experiments using the DARwIn miniature humanoid robot developed by RoMeLa at Virginia Tech as the test platform. The simulations proved successful and provided more insight to understanding instabilities that can occur for different gait generation methods. The physical experiments worked well for non-walking motions, but because of insufficient controllability in the joint actuators of the humanoid robot used for the experiment, the high loads during walking motions prevented them from proper testing. The algorithms used in this work could also be expanded to legged robots or entirely different platforms that depend on stability and can use the ZMP as a stability criterion. One of the primary contributions of this work was showing that an entire reference motion could be stabilized using a single set of closed form solutions and equations. Previous work by others considered optimization functions and numeric schemes to stabilize all or a portion of a gait. Instead, the Analytical Motion Filter gives a direct relationship between the input reference motion and the resulting filtered output motion.
Ph. D.

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Hauser, Kris. "Motion planning for legged and humanoid robots /." May be available electronically:, 2008. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.

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Zorjan, Maja. "Contribution to the design optimization of humanoid leg kinematics." Versailles-St Quentin en Yvelines, 2012. http://www.theses.fr/2012VERS0013.

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La plupart des robots humanoïdes qui existent possèdent une cinématique orthogonale de la jambe, où toutes les articulations de tangage, roulis et lacet sont orthogonales deux à deux et alignées respectivement le long des axes latéral, longitudinal et vertical du corps de robot. L'articulation de la hanche est composée de trois degrés de liberté. Leurs axes de rotation sont mutuellement orthogonaux et constituent un référentiel cartésien. Généralement, l’ordre des axes de la hanche est classique dans les robots humanoïdes, c'est-à-dire, de la hanche aux pieds : lacet, roulis et tangage. Les recherches dans le cadre de cette thèse s’intéressent à l’influence d’un changement de l’orientation des axes de rotation au niveau de la hanche. Les études ont été menées dans le cas de mouvements à double support (flexion/extension des genoux, avec ou sans articulation de la colonne vertébrale, avec charge additionnelle dans les mains, et déhanchements) et dans le cas de mouvements de locomotion (marche avant et rotation sur place). Ces études ont été réalisées en considérant un ordre standard des articulations (lacet, roulis et tangage). Afin de comparer les différentes configurations, plusieurs critères ont été utilisés : puissance moyenne, course angulaire, couple maximal, relation vitesse angulaire/couple. Les résultats de cette étude soulignent l’intérêt d’orienter les axes de la hanche différemment afin d’obtenir une meilleure répartition de la puissance mise en jeu et de faciliter la sélection des moteurs à utiliser
Most of the existing humanoid robots have usual orthogonal leg joint kinematics where all pitch, roll and yaw joints are mutually orthogonal and aligned along lateral, longitudinal and vertical axes of the robot's body, respectively. The hip joint consists of three single DoFs (degree of freedom). Their axes of rotation are mutually orthogonal and constitute Cartesian coordinate frame. Usually, the hip joint axes are successively ordered (from hip to foot) in a standard way for humanoid robots i. E. Hip yaw, hip roll and hip pitch. This research investigates the influence of a different layout and orientation of hip rotation axes. Investigations were carried out on double support motions (knee flexion/extension, knee flexion with articulated spine, knee flexion with additional load in the hands and swaying hips motion) and locomotion (walking forward and turn-in-place). Study was conducted for standard joints order (yaw, roll and pitch). To analyze differences, average power, angle range, magnitude of maximal torque and torque versus angular speed in the different configurations are compared. In all simulations the complete dynamics of the robot was taken into account. This study can help to orient hip axes to achieve better power distribution between hip joint motors and make better motor selection

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MIRABEL, JOSEPH. "Object manipulation by humanoid robots : Constrained motion planning using a graph of constraints applied to objectmanipulation by humanoid robots." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-156314.

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Humanoid robots have been an active field of research during the past few decades owing to the wide variety of motions and interactions possible via Humanoid. Nevertheless, planning motions is still challenging in many cases. This thesis tackles the problem of object manipulation. A graph of constraints is introduced to transform object manipulation tasks in sequences of constraints. Then, a constrained motion planner, using the graph of constraints, is used to find a suitable statically balanced path for a sliding robot. Affordance is used to provide the required information to build the graph of constraints. Analgorithm based on Rapidly exploring Random Tree navigates through the graph of constraints. Basic experiments of this method were performed with the humanoid robot HRP-2.
Humanoida robotar har varit ett aktivt området för forskning under de senaste årtiondena på grund av deras stora möjligheter för rörelse roch interaktioner. Rörelseplanering är fortfarande problematiskt i många fall. Detta examensarbete tar itu med problemet med objektmanipulation. En graf av bivillkor införs för att omvandla objektmanipulationsupgifter till sekvenser av bivillkor. Denna graf används av rörelseplanerare för att hitta en lämplig statiskt balanserade väg för en glidande robot. Affordance används för att tillhandahålla den information som krävs för att bygga upp grafen och en algoritm baserad på Rapidly exploring Random Tree används för att navigera genom grafen. Grundläggande försök med denna metod utförts med den humanoidaroboten HRP-2.

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Aspernäs, Andreas. "Human-like Crawling for Humanoid Robots : Gait Evaluation on the NAO robot." Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-78761.

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Human-robot interaction (HRI) is the study of how we as humans interact and communicate with robots and one of its subfields is working on how we can improve the collaboration between humans and robots. We need robots that are more user friendly and easier to understand and a key aspect of this is human-like movements and behavior. This project targets a specific set of motions called locomotion and tests them on the humanoid NAO robot. A human-like crawling gait was developed for the NAO robot and compared to the built-in walking gait through three kinds of experiments. The first one to compare the speed of the two gaits, the second one to estimate their sta- bility, and the third to examine how long they can operate by measuring the power consumption and temperatures in the joints. The results showed the robot was significantly slower when crawling compared to walking, and when still the robot was more stable while standing than on all-fours. The power consumption remained essentially the same, but the crawling gait ended up having a shorter operational time due to higher temperature increase in the joints. While the crawling gait has benefits of having a lower profile then the walking gait and could therefore more easily pass under low hanging obsta- cles, it does have major issues that needs to be addressed to become a viable solution. Therefore these are important factors to consider when developing gaits and designing robots, and motives further research to try and solve these problems.

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Brooks, Douglas A. "Towards quantifying upper-arm rehabilitation metrics for children through interaction with a humanoid robot." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/48970.

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The objective of this research effort is to further rehabilitation techniques for children by developing and validating the core technologies needed to integrate therapy instruction with child-robot play interaction in order to improve upper-arm rehabilitation. Using computer vision techniques such as Motion History Imaging (MHI), Multimodal Mean, edge detection, and Random Sample Consensus (RANSAC), movements can be quantified through robot observation. Also incorporating three-dimensional data obtained via an infrared projector coupled with a Principle Component Analysis (PCA), depth information can be utilized to create a robust algorithm. Finally, utilizing prior knowledge regarding exercise data, physical therapeutic metrics, and novel approaches, a mapping to therapist instructions can be created allowing robotic feedback and intelligent interaction.

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Bozcuoglu, Asil Kaan. "A Developmental Grasp Learning Scheme For Humanoid Robots." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614835/index.pdf.

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While an infant is learning to grasp, there are two key processes that she uses for leading a successful development. In the first process, infants use an intuitional approach where the hand is moved towards the object to create an initial contact regardless of the object properties. The contact is followed by a tactile grasping phase where the object is enclosed by the hand. This intuitive grasping behavior leads an grasping mechanism, which utilizes visual input and incorporates this into the grasp plan. The second process is called scaffolding, a guidance by stating how to accomplish the task or modifying its behaviors by interference. Infants pay attention to such guidance and understand the indication of important features of an object from 9 months of age. This supervision mechanism plays an important role for learning how to grasp certain objects in a proper way. To simulate these behavioral findings, a reaching and a tactile grasping controller was implemented on iCub humanoid robot which allowed it to reach an object from different directions, and enclose its fingers to cover the object. With these, a human-like grasp learning for iCub is proposed. Namely, the first step is an unsupervised learning where the robot is experimenting how to grasp objects. The second step is supervised learning phase where a caregiver modifies the end-effectors position when the robot is mistaken. By doing several experiments for two different grasping styles, we observe that the proposed methodology shows a better learning rate comparing to the scaffolding-only learning mechanism.

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Esteves, Jaramillo Claudia Elvira. "Motion Planning : from Digital Actors to Humanoid Robots." Phd thesis, Institut National Polytechnique de Toulouse - INPT, 2007. http://tel.archives-ouvertes.fr/tel-00145201.

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Le but de ce travail est de développer des algorithmes de planification de mouvement pour des figures anthropomorphes en tenant compte de la géométrie, de la cinématique et de la dynamique du mécanisme et de son environnement.
Nous proposons une approche à trois étages au problème de la planification de mouvements pour des figures anthropomorphes qui manipulent des objets encombrants tout en marchant. Dans le processus, plusieurs problèmes ainsi que des propositions pour les résoudre, sont présentés. Ceux sont principalement l'évitement tri-dimensionnel des obstacles, la manipulation des objets à deux mains, la manipulation coopérative des objets et la combinaison de comportements hétérogènes.
La contribution principale est la modélisation du problème de la génération automatique des mouvements de manipulation et de locomotion dans le contexte de mécanismes bipèdes. Les bonnes performances du planificateur sont validées avec des mécanismes différents, tant virtuels que physiques.

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Trifan, Alina Liliana. "Development of a vision system for humanoid robots." Master's thesis, Universidade de Aveiro, 2011. http://hdl.handle.net/10773/7173.

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Esteves, Jaramillo Claudia Elvira Laumond Jean-Paul. "Motion planning from digital actors to humanoid robots /." Toulouse : INP Toulouse, 2007. http://ethesis.inp-toulouse.fr/archive/00000454.

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Al-Hami, Motaz Abdul Aziz. "Towards A Better Pose Understanding for Humanoid Robots." Diss., Temple University Libraries, 2016. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/368043.

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Computer and Information Science
Ph.D.
Towards A Better Pose Understanding for Humanoid Robots by Mo’taz Al-Hami Humanoid Robots have been showing a rapidly increasing ability to interact with their surrounding environment. A large spectrum of such interactions focuses on how robots can mimic human postures and posture related actions, like walking, grasping, standing and sitting on objects. In many cases the robot has a clear and well defined description of general postures related to a given task. The topic of this thesis focuses on exploring human poses of humanoid robots and in images. Such understanding and learning will help to understand 3D pose modeling, which can support humanoid robots in their interaction with the environment. In chapter one, we focus on generating physical poses for a NAO humanoid robot. To generate poses interactively, the poses should be controlled to satisfy any potential interaction with the environment. In this chapter, a simulated and real humanoid robot "NAO" is utilized to discover a fitness-based optimal sitting pose performed on various types of objects, varying in shape and height. Using an initial set of random valid sitting poses as the input generation, a genetic algorithm (GA) is applied to construct the fitness-based optimal pose for the robot to fit well on the object. The fitness criteria reflecting pose stability (i.e. how feasible the pose is based on real world physical limitation) converts poses into numerical stability level. The feasibility of the proposed approach is measured through a simulated environment using the V-Rep simulator. The real "NAO" robot performs the results generated by the simulation for real world evaluation. Next, in chapter two we focus on generating 3D pose models using only query keywords. In this chapter, we propose a self-motivated approach to learn 3D human pose conformation without using a priori knowledge. The proposed framework benefits from known 2D human pose estimators using still images and continue to build a sufficient approximate pose representing a group of images. With such approximation we can build an approximate 3D model representing this pose conformation. The proposed framework steps forward towards a self-motivated conceptual analysis and recognition in humanoid robots. The goal for this framework is to relate query keywords with 3D human poses. We evaluate our approach with different query keywords representing a specific human pose. The results confirm the ability to learn 3D human poses without a priori knowledge. Chapter three proposes a 3D analysis approach for 3D modeling. Our approach utilizes a human-pose based 3D shape context model for matching human-poses in 3D space, and filter them using a hierarchical binary clustering approach. The performance of this approach is evaluated with different query keywords. Recovering a 3D human-pose in form of an abstracted skeleton from a 2D image suffers from loss of depth information. Assuming the projected pose is represented by a set of 2D landmarks capturing the pose limbs, recovering back the original 3D locations is an ill posed problem. To recover a 3D configuration, camera localization in 3D space plays a major role, an inaccurate camera localization might mislead the recovery process. In Chapter four, we propose a 3D camera localization model using only human-pose appearance in a single 2D image (i.e. the set of 2D landmarks). We apply a supervised multi class logistic regression to assign the camera location in 3D space. In the learning process, we assume a set of predefined labeled camera locations. The features we train consist of relative length of limbs and 2D shape context. The goal is to build a relation between these projected landmarks and the camera location in 3D space. This kind of analysis allows us to reconstruct 3D poses based on the 2D projection only without any predefined camera parameters. We test our model on a set of real images showing a variety of camera locations.
Temple University--Theses

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Thunberg, Sofia. "Investigating the Social Influence of Different Humanoid Robots." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-139347.

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The aim with this thesis were to investigate social influence of the two humanoid robots, NAO and Pepper. The research questions were if there were a difference in human social acceptance, in social influence and in influence on human decision making between NAO and Pepper. To answer these questions, an experiment using the Wizard of Oz-method were used with 36 participant, 18 in each group, interacted with NAO or Pepper. Afterwards two questionnaires, NARS and GODSPEED, were answered and an additional interview were held with the participants. The result showed a significant difference on GODSPEED, where NAO indicates to have a higher amount of social influence on the participants then Pepper. The result for NARS were not significant. The result from the decisions made during the experiment indicated that humans follow NAO more than Pepper, a result that got more explained and understandable during the interviews. For future studies there would be interesting to test the scenario with a larger selection and also with a more natural Wizard of Oz-design.

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Naveau, Maximilien. "Advanced human inspired walking strategies for humanoid robots." Thesis, Toulouse 3, 2016. http://www.theses.fr/2016TOU30188/document.

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Cette thèse traite du problème de la locomotion des robots humanoïdes dans le contexte du projet européen KoroiBot. En s'inspirant de l'être humain, l'objectif de ce projet est l'amélioration des capacités des robots humanoïdes à se mouvoir de façon dynamique et polyvalente. Le coeur de l'approche scientifique repose sur l'utilisation du controle optimal, à la fois pour l'identification des couts optimisés par l'être humain et pour leur mise en oeuvre sur les robots des partenaires roboticiens. Cette thèse s'illustre donc par une collaboration à la fois avec des mathématiciens du contrôle et des spécialistes de la modélisation des primitives motrices. Les contributions majeures de cette thèse reposent donc sur la conception de nouveaux algorithmes temps-réel de contrôle pour la locomotion des robots humanoïdes avec nos collégues de l'université d'Heidelberg et leur intégration sur le robot HRP-2. Deux contrôleurs seront présentés, le premier permettant la locomotion multi-contacts avec une connaissance a priori des futures positions des contacts. Le deuxième étant une extension d'un travail réalisé sur de la marche sur sol plat améliorant les performances et ajoutant des fonctionnalitées au précédent algorithme. En collaborant avec des spécialistes du mouvement humain nous avons implementé un contrôleur innovant permettant de suivre des trajectoires cycliques du centre de masse. Nous présenterons aussi un contrôleur corps-complet utilisant, pour le haut du corps, des primitives de mouvements extraites du mouvement humain et pour le bas du corps, un générateur de marche. Les résultats de cette thèse ont été intégrés dans la suite logicielle "Stack-of-Tasks" du LAAS-CNRS
This thesis covers the topic of humanoid robot locomotion in the frame of the European project KoroiBot. The goal of this project is to enhance the ability of humanoid robots to walk in a dynamic and versatile fashion as humans do. Research and innovation studies in KoroiBot rely on optimal control methods both for the identification of cost functions used by human being and for their implementations on robots owned by roboticist partners. Hence, this thesis includes fruitful collaborations with both control mathematicians and experts in motion primitive modeling. The main contributions of this PhD thesis lies in the design of new real time controllers for humanoid robot locomotion with our partners from the University of Heidelberg and their integration on the HRP-2 robot. Two controllers will be shown, one allowing multi-contact locomotion with a prior knowledge of the future contacts. And the second is an extension of a previous work improving performance and providing additional functionalities. In a collaboration with experts in human motion we designed an innovating controller for tracking cyclic trajectories of the center of mass. We also show a whole body controller using upper body movement primitives extracted from human behavior and lower body movement computed by a walking pattern generator. The results of this thesis have been integrated into the LAAS-CNRS "Stack-of-Tasks" software suit

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SUBBURAMAN, RAJESH. "Fall Prediction and Controlled Fall for Humanoid Robots." Doctoral thesis, Università degli studi di Genova, 2019. http://hdl.handle.net/11567/939791.

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Humanoids which resemble humans in their body structure and degrees of freedom are anticipated to work like them within infrastructures and environments constructed for humans. In such scenarios, even humans who have exceptional manipulation, balancing, and locomotion skills are vulnerable to fall, humanoids being their approximate imitators are no exception to this. Furthermore, their high center of gravity position in relation to their small support polygon makes them more prone to fall, unlike other robots such as quadrupeds. The consequences of these falls are so devastating that it can instantly annihilate both the robot and its surroundings. This has become one of the major stumbling blocks which humanoids have to overcome to operate in real environments. As a result, in this thesis, we have strived to address the imminent fall over of humanoids by developing different control techniques. The fall over problem as such can be divided into three subissues: fall prediction, controlled fall, and its recovery. In the presented work, the first two issues have been addressed, and they are presented in three parts. First, we define what is fall over for humanoids, different sources for it to happen, the effect fall over has both on the robot and to its surroundings, and how to deal with them. Following which, we give a brief introduction to the overall system which includes both the hardware and software components which have been used throughout the work for varied purposes. Second, the first sub-issue is addressed by proposing a generic method to predict the falling over of humanoid robots in a reliable, robust, and agile manner across various terrains, and also amidst arbitrary disturbances. The aforementioned characteristics are strived to attain by proposing a prediction principle inspired by the human balance sensory systems. Accordingly, the fusion of multiple sensors such as inertial measurement unit and gyroscope (IMU), foot pressure sensor (FPS), joint encoders, and stereo vision sensor, which are equivalent to the human’s vestibular, proprioception, and vision systems are considered. We first define a set of feature-based fall indicator variables (FIVs) from the different sensors, and the thresholds for those FIVs are extracted analytically for four major disturbance scenarios. Further, an online threshold interpolation technique and an impulse adaptive counter limit are proposed to manage more generic disturbances. For the generalized prediction process, both the instantaneous and cumulative sum of each FIVs are normalized, and a suitable value is set as the critical limit to predict the fall over. To determine the best combination and the usefulness of multiple sensors, the prediction performance is evaluated on four different types of terrains, in three unique combinations: first, each feature individually with their respective FIVs; second, an intuitive performance based (PF); and finally, Kalman filter based (KF) techniques, which involve the usage of multiple features. For PF and KF techniques, prediction performance evaluations are carried out with and without adding noise. Overall, it is reported that KF performs better than PF and individual sensor features under different conditions. Also, the method’s ability to predict fall overs during the robot’s simple dynamic motion is also tested and verified through simulations. Experimental verification of the proposed prediction method on flat and uneven terrains was carried out with the WALK-MAN humanoid robot. Finally, in reference to the second sub-issue, i.e., the controlled fall, we propose two novel fall control techniques based on energy concepts, which can be applied online to mitigate the impact forces incurred during the falling over of humanoids. Both the techniques are inspired by the break-fall motions, in particular, Ukemi motion practiced by martial arts people. The first technique reduces the total energy using a nonlinear control tool, called energy shaping (ES) and further distributes the reduced energy over multiple contacts by means of energy distribution polygons (EDP). We also include an effective orientation control to safeguard the end-effectors in the event of ground impacts. The performance of the proposed method is numerically evaluated by dynamic simulations under the sudden falling over scenario of the humanoid robot for both lateral and sagittal falls. The effectiveness of the proposed ES and EDP concepts are verified by diverse comparative simulations regarding total energy, distribution, and impact forces. Following the first technique, we proposed another controller to generate an online rolling over motion based on the hypothesis that multi-contact motions can reduce the impact forces even further. To generate efficient rolling motion, critical parameters are defined by the insights drawn from a study on rolling, which are contact positions and attack angles. In addition, energy-injection velocity is proposed as an auxiliary rolling parameter to ensure sequential multiple contacts in rolling. An online rolling controller is synthesized to compute the optimal values of the rolling parameters. The first two parameters are to construct a polyhedron, by selecting suitable contacts around the humanoid’s body. This polyhedron distributes the energy gradually across multiple contacts, thus called energy distribution polyhedron. The last parameter is to inject some additional energy into the system during the fall, to overcome energy drought and tip over successive contacts. The proposed controller, incorporated with energy injection, minimization, and distribution techniques result in a rolling like motion and significantly reduces the impact forces, and it is verified in numerical experiments with a segmented planar robot and a full humanoid model.

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Hoggenmueller, Marius. "Urban Robotic Interfaces: Designing for Encounters with Non-Humanoid Robots in Cities." Thesis, The University of Sydney, 2022. https://hdl.handle.net/2123/29327.

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The contemporary city is increasingly mediated by computing and automation, promising to improve the quality of urban life. Urban robots represent the next generation of urban technologies, which are capable of sensing, autonomously operating and physically manipulating the urban environment. However, while research in engineering led the foundation for the technological development of urban robots, their human-centred design, including the design of the interfaces to facilitate encounters and interactions between humans and urban robots, has been less explored. Furthermore, it remains an open question how to systematically prototype these complex technologies in urban environments. The research aim of this thesis is to advance the understanding of the design space of urban robotic interfaces. To achieve this aim, this publication-based thesis employs a research in and through design approach, using methods from human-computer interaction. To seek a deeper understanding of the opportunities and challenges of designing urban robotic interfaces, existing urban interfaces and new ones emerging out of the intrinsic characteristics of urban robots are reviewed and classified. This review lays the foundation for the two implemented case studies, which form the core part of this thesis: First, a slow-moving urban robot that draws with chalk on the ground was designed and deployed as an urban probe to explore the potential of physicalised displays, and to investigate social interactions around urban robots. For the second case study, we guided the design of a low-resolution lighting display for a fully functional shared autonomous vehicle. The case studies consist of two empirical studies each, which were conducted in the wild and in the lab, respectively. The findings that emerged from this research expand the design space of urban robotic interfaces and shed light on the challenges in prototyping by offering conceptual, empirical and methodological contributions.

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Sleiman, Maya. "New actuation technologies for humanoid robotics and assistive devices." Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPAST110.

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L’actionnement hydraulique a prouvé sacapacité à fournir des forces élevées dans un volume léger et compact. Pour cette raison, plusieurs robots humanoïdes utilisent cette technologie pour démontrer leur performance. Mais, cetactionnement s’accompagne de problèmes de fuiteliés à la présence de tubes hydrauliques. Cettethèse concentre sur la résolution de ce problèmeen adoptant deux approches. Dans la première, lespièces internes sont conçues selon une approchebio-inspirée pour conduire l’huile. Les pièces sontredéveloppées en forme de coquille avec des tubesen plastique intégrés, imprimés en 3D, puis moulés avec un matériau composite en carbone pourles renforcer. La deuxième solution vise à créer desunités de production d’énergie ponctuelles au niveau des joints. À cette fin, un actionneur servoélectro-hydraulique breveté est développé, modélisé et conçu. Les premiers prototypes sont fabriqués, testés et validés
During the past years, hydraulic actuation has proven its capacity to deliver high forces ina lightweight and compact volume. For this reason,several humanoid robots make use of this technology to demonstrate performance in heavy-dutyactivities. Basically, hydraulic actuation is accompanied by leak problems linked to the presence ofhydraulic tubes. This research focuses on solvingthis problem by adopting two approaches. Adopting the first solution, internal parts are designedin a bio-inspired approach to drive pressurized oilto the actuated joints. All robotic parts are redeveloped in a shell design with integrated plastictubes, 3D printed, then molded with carbon composite material for strengthening. The second solution aims to create punctual power generationunits at the actuation joints. For this aim, a patented Servo Electro-Hydraulic Actuator is developed, modeled, and designed. The first prototypesare manufactured, tested, and validated

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Mirko, Raković. "Sinteza i realizacija dvonožnog hoda putem primitiva." Phd thesis, Univerzitet u Novom Sadu, Fakultet tehničkih nauka u Novom Sadu, 2013. http://www.cris.uns.ac.rs/record.jsf?recordId=85600&source=NDLTD&language=en.

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U tezi je prikazan novi metod za sintezu i realizaciju dvonožnogveštačkog hoda koji se zasniva na upotrebi jednostavnih pokreta čijimje kombinovanjem moguće realizovati kompleksne pokrete kao što jehod, a čiji se parametri mogu menjati tokom kretanja. Time je omogućenoda se na osnovu informacija o nameravanom kretanju i stanja okolineizvrši sinteza kretanja izborom i kombinacijom jednostavnihbazičnih pokreta koje se nazivaju primitivi. Takođe je omogućeno da se,tokom izvršavanja hoda bez njegovog prekida, menjaju parametrikretanja kao što su brzina hoda, dužina koraka, pravac kretanja ivisina podizanja noge tokom prenosne faze. Potvrda je data krozeksperimentalne rezultate koji su sprovedeni simulacijom nadinamičkom modelu humanoidnog robota.
This dissertation presents new method for the synthesis and realization ofbiped artificial walk based on the use of simple movements that can becombined in order to achieve complex movements such as walk, whereas itis possible to change the motion parameters at any time. It means that,based on the information about intended movement and current state of theenvironment, it is possible to synthesize motion by selecting and tying simplemovements, i.e. motion primitives. It also enables the robot to changewalking parameters online such as walking speed, direction of walk, footlength during swing phase and step length. Proof of this method is given byexperimental results obtained during the simulation on a dynamic model ofhumanoid robot.

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Yik, Tak Fai Computer Science &amp Engineering Faculty of Engineering UNSW. "Locomotion of bipedal humanoid robots: planning and learning to walk." Awarded by:University of New South Wales. Computer Science & Engineering, 2007. http://handle.unsw.edu.au/1959.4/40446.

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Pure reinforcement learning does not scale well to domains with many degrees of freedom and particularly to continuous domains. In this thesis, we introduce a hybrid method in which a symbolic planner constructs all approximate solution to a control problem.. Subsequently, a numerical optimisation algorithm is used to refine the qualitative plan into an operational policy. The method is demonstrated on the problem of learning a stable walking gait for a bipedal robot. The contributions of this thesis are as follows. Firstly, the thesis proposes a novel way to generate gait patterns by using a genetic algorithm to generate walking gaits for a humanoid robot using zero moment point as the stability criterion. This is validated on physical robot. Second, we propose an innovative generic learning method that utilises the trainer's domain knowledge about the task to accelerate learning and extend the capabilities of the learning algorithm. The proposed method, which takes advantage of domain knowledge and combines symbolic planning and learning to accelerate and reduce the search space of the learning problem, is tested on a bipedal humanoid robot learning to walk. Finally, it is shown that the extended capability of the learning algorithm handles high complexity learning tasks in the physical world with experimental verification on a physical robot.

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Gielniak, Michael Joseph. "Adaptation of task-aware, communicative variance for motion control in social humanoid robotic applications." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/43591.

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An algorithm for generating communicative, human-like motion for social humanoid robots was developed. Anticipation, exaggeration, and secondary motion were demonstrated as examples of communication. Spatiotemporal correspondence was presented as a metric for human-like motion, and the metric was used to both synthesize and evaluate motion. An algorithm for generating an infinite number of variants from a single exemplar was established to avoid repetitive motion. The algorithm was made task-aware by including the functionality of satisfying constraints. User studies were performed with the algorithm using human participants. Results showed that communicative, human-like motion can be harnessed to direct partner attention and communicate state information. Furthermore, communicative, human-like motion for social robots produced by the algorithm allows humans partners to feel more engaged in the interaction, recognize motion earlier, label intent sooner, and remember interaction details more accurately.

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de, Azambuja Ricardo. "Action learning experiments using spiking neural networks and humanoid robots." Thesis, University of Plymouth, 2018. http://hdl.handle.net/10026.1/10767.

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The way our brain works is still an open question, but one thing seems to be clear: biological neural systems are computationally powerful, robust and noisy. Natural nervous system are able to control limbs in different scenarios with high precision. As neural networks in living beings communicate through spikes, modern neuromorphic systems try to mimic them by using spike-based neuron models. This thesis is focused on the advancement of neurorobotics or brain inspired robotic arm controllers based on artificial neural network architectures. The architecture chosen to implement those controllers was the spike neuron version of Reservoir Computing framework, called Liquid State Machines. The main goal is to explore the possibility of using brain inspired neural networks to control a robot by demonstration. Moreover, it aims to achieve systems robust to environmental noise and internal structure destruction presenting a graceful degradation. As the validation, a series of action learning experiments are presented where simulated robotic arms are controlled. The investigation starts with a 2 degrees of freedom arm and moves to the research version of the Rethink Robotics Inc. collaborative humanoid robot Baxter. Moreover, a proof-of- concept experiment is also done using the real Baxter robot. The results show Liquid State Machines, when endowed with an extra external feedback loop, can be also employed to control more complex humanoid robotic arms than a simple planar 2 degrees of freedom one. Additionally, the new parallel architecture presented here was capable to withstand noise and internal destruction better than a simple use of multiple columns also presenting a graceful degradation behaviour.

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Jagtap, Vinayak V. "A Walking Controller for Humanoid Robots using Virtual Force." Digital WPI, 2019. https://digitalcommons.wpi.edu/etd-dissertations/581.

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Current state-of-the-art walking controllers for humanoid robots use simple models, such as Linear Inverted Pendulum Mode (LIPM), to approximate Center of Mass(CoM) dynamics of a robot. These models are then used to generate CoM trajectories that keep the robot balanced while walking. Such controllers need prior information of foot placements, which is generated by a walking pattern generator. While the robot is walking, any change in the goal position leads to aborting the existing foot placement plan and re-planning footsteps, followed by CoM trajectory generation. This thesis proposes a tightly coupled walking pattern generator and a reactive balancing controller to plan and execute one step at a time. Walking is an emergent behavior from such a controller which is achieved by applying a virtual force in the direction of the goal. This virtual force, along with external forces acting on the robot, is used to compute desired CoM acceleration and the footstep parameters for only the next step. Step location is selected based on the capture point, which is a point on the ground at which the robot should step to stay balanced. Because each footstep location is derived as needed based on the capture point, it is not necessary to compute a complete set of footsteps. Experiments show that this approach allows for simpler inputs, results in faster operation, and is inherently immune to external perturbing and other reaction forces from the environment. Experiments are performed on Boston Dynamic's Atlas robot and NASA's Valkyrie R5 robot in simulation, and on Atlas hardware.

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Bartholomew, Paul D. "Optimal behavior composition for robotics." Thesis, Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/51872.

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The development of a humanoid robot that mimics human motion requires extensive programming as well as understanding the motion limitations of the robot. Programming the countless possibilities for a robot’s response to observed human motion can be time consuming. To simplify this process, this thesis presents a new approach for mimicking captured human motion data through the development of a composition routine. This routine is built upon a behavior-based framework and is coupled with optimization by calculus to determine the appropriate weightings of predetermined motion behaviors. The completion of this thesis helps to fill a void in human/robot interactions involving mimicry and behavior-based design. Technological advancements in the way computers and robots identify human motion and determine for themselves how to approximate that motion have helped make possible the mimicry of observed human subjects. In fact, many researchers have developed humanoid systems that are capable of mimicking human motion data; however, these systems do not use behavior-based design. This thesis will explain the framework and theory behind our optimal behavior composition algorithm and the selection of sinusoidal motion primitives that make up a behavior library. This algorithm breaks captured motion data into various time intervals, then optimally weights the defined behaviors to best approximate the captured data. Since this routine does not reference previous or following motion sequences, discontinuities may exist between time intervals. To address this issue, the addition of a PI controller to regulate and smooth out the transitions between time intervals will be shown. The effectiveness of using the optimal behavior composition algorithm to create an approximated motion that mimics capture motion data will be demonstrated through an example configuration of hardware and a humanoid robot platform. An example of arm motion mimicry will be presented and includes various image sequences from the mimicry as well as trajectories containing the joint positions for both the human and the robot.

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Sugiura, Hisashi [Verfasser]. "Real World Collision Avoidance for Humanoid Robots / Hisashi Sugiura." Aachen : Shaker, 2010. http://d-nb.info/1081885483/34.

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Perrin, Nicolas. "Footstep planning for humanoid robots: discrete and continuous approaches." Phd thesis, Institut National Polytechnique de Toulouse - INPT, 2011. http://tel.archives-ouvertes.fr/tel-00647469.

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Dans cette thèse nous nous intéressons à deux types d'approches pour la planification de pas pour robots humanoïdes : d'une part les approches discrètes où le robot n'a qu'un nombre fini de pas possibles, et d'autre part les approches où le robot se base sur des zones de faisabilité continues. Nous étudions ces problèmes à la fois du point de vue théorique et pratique. En particulier nous décrivons deux méthodes originales, cohérentes et efficaces pour la planification de pas, l'une dans le cas discret (chapitre 5) et l'autre dans le cas continu (chapitre 6). Nous validons ces méthodes en simulation ainsi qu'avec plusieurs expériences sur le robot HRP-2.

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Wang, Jiuguang. "Numerical Nonlinear Robust Control with Applications to Humanoid Robots." Research Showcase @ CMU, 2015. http://repository.cmu.edu/dissertations/630.

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Robots would be much more useful if they could be more robust. Systems that can tolerate variability and uncertainty are called robust and the design of robust feedback controllers is a difficult problem that has been extensively studied for the past several decades. In this thesis, we aim to provide a quantitative measure of performance and robustness in control design under an optimization framework, producing controllers robust against parametric system uncertainties, external disturbances, and unmodeled dynamics. Under the H1 framework, we formulate the nonlinear robust control problem as a noncooperative, two-player, zero-sum, differential game, with the Hamilton-Jacobi-Isaacs equation as a necessary and sufficient condition for optimality. Through a spectral approximation scheme, we develop approximate algorithms to solve this differential game on the foundation of three ideas: global solutions through value function approximation, local solutions with trajectory optimization, and the use of multiple models to address unstructured uncertainties. Our goal is to introduce practical algorithms that are able to address complex system dynamics with high dimensionality, and aim to make a novel contribution to robust control by solving problems on a complexity scale untenable with existing approaches in this domain. We apply this robust control framework to the control of humanoid robots and manipulation in tasks such as operational space control and full-body push recovery.

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VAZHAPILLI, SURESHBABU ANAND. "Design and development of robust hands for humanoid robots." Doctoral thesis, Università degli studi di Genova, 2018. http://hdl.handle.net/11567/930270.

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Hale, Joshua G. "Biomimetic motion synthesis for synthetic humanoids." Thesis, University of Glasgow, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.270966.

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Geisert, Mathieu. "Optimal control and machine learning for humanoid and aerial robots." Thesis, Toulouse, INSA, 2018. http://www.theses.fr/2018ISAT0011/document.

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Quelle sont les points communs entre un robot humanoïde et un quadrimoteur ? Et bien, pas grand-chose… Cette thèse est donc dédiée au développement d’algorithmes permettant de contrôler un robot de manière dynamique tout en restant générique par rapport au model du robot et à la tâche que l’on cherche à résoudre. Le contrôle optimal numérique est pour cela un bon candidat. Cependant il souffre de plusieurs difficultés comme un nombre important de paramètres à ajuster et des temps de calcul relativement élevés. Ce document présente alors plusieurs améliorations permettant d’atténuer ces difficultés. D’un côté, l’ordonnancement des différentes tâches sous la forme d’une hiérarchie et sa résolution avec un algorithme adapté permet de réduire le nombre de paramètres à ajuster. D’un autre côté, l’utilisation de l’apprentissage automatique afin d’initialiser l’algorithme d’optimisation ou de générer un modèle simplifié du robot permet de fortement diminuer les temps de calcul
What are the common characteristics of humanoid robots and quadrotors? Well, not many… Therefore, this thesis focuses on the development of algorithms allowing to dynamically control a robot while staying generic with respect to the model of the robot and the task that needs to be solved. Numerical optimal control is good candidate to achieve such objective. However, it suffers from several difficulties such as a high number of parameters to tune and a relatively important computation time. This document presents several ameliorations allowing to reduce these problems. On one hand, the tasks can be ordered according to a hierarchy and solved with an appropriate algorithm to lower the number of parameters to tune. On the other hand, machine learning can be used to initialize the optimization solver or to generate a simplified model of the robot, and therefore can be used to decrease the computation time

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Leitner, Jürgen. "From vision to actions: Towards adaptive and autonomous humanoid robots." Thesis, Università della Svizzera Italiana, 2014. https://eprints.qut.edu.au/90178/2/2014INFO020.pdf.

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Although robotics research has seen advances over the last decades robots are still not in widespread use outside industrial applications. Yet a range of proposed scenarios have robots working together, helping and coexisting with humans in daily life. In all these a clear need to deal with a more unstructured, changing environment arises. I herein present a system that aims to overcome the limitations of highly complex robotic systems, in terms of autonomy and adaptation. The main focus of research is to investigate the use of visual feedback for improving reaching and grasping capabilities of complex robots. To facilitate this a combined integration of computer vision and machine learning techniques is employed. From a robot vision point of view the combination of domain knowledge from both imaging processing and machine learning techniques, can expand the capabilities of robots. I present a novel framework called Cartesian Genetic Programming for Image Processing (CGP-IP). CGP-IP can be trained to detect objects in the incoming camera streams and successfully demonstrated on many different problem domains. The approach requires only a few training images (it was tested with 5 to 10 images per experiment) is fast, scalable and robust yet requires very small training sets. Additionally, it can generate human readable programs that can be further customized and tuned. While CGP-IP is a supervised-learning technique, I show an integration on the iCub, that allows for the autonomous learning of object detection and identification. Finally this dissertation includes two proof-of-concepts that integrate the motion and action sides. First, reactive reaching and grasping is shown. It allows the robot to avoid obstacles detected in the visual stream, while reaching for the intended target object. Furthermore the integration enables us to use the robot in non-static environments, i.e. the reaching is adapted on-the- fly from the visual feedback received, e.g. when an obstacle is moved into the trajectory. The second integration highlights the capabilities of these frameworks, by improving the visual detection by performing object manipulation actions.

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48

Orthey, Andreas. "Exploiting structure in humanoid motion planning." Phd thesis, Toulouse, INPT, 2015. http://oatao.univ-toulouse.fr/14685/1/orthey.pdf.

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If humanoid robots should work along with humans and should be able to solve repetitive tasks, we need to enable them with a skill to autonomously plan motions. Motion planning is a longstanding core problem in robotics, and while its algorithmic foundation has been studied in depth, motion planning is still an NP-hard problem lacking efficient solutions. We want to open up a new perspective on the problem by highlighting its structure: the behavior of the robot, the mechanical system of the robot, and the environment of the robot. We will investigate the hypothesis that each structural component can be exploited to create more efficient motion planning algorithms. We present three algorithms exploiting structure, based on geometrical and topological arguments: first, we exploit the behavior of a walking robot by studying the feasibility of footstep transitions. The resulting algorithm is able to plan footsteps avoiding up to 60 objects on a 6 square meters planar surface. Second, we exploit the mechanical system of a humanoid robot by studying the linear linkage structures of its arms and legs. We introduce the concept of an irreducible motion, which is a completeness-preserving dimensionality reduction technique. The resulting algorithm is able to find motions in narrow environments, where previous sampling-based methods could not be applied. Third, we exploit the environment by reasoning about the topological structure of contact transitions. We show that analyzing the environment is an efficient method to precompute relevant information for efficient motion planning. Based on those results, we come to the conclusion that exploiting structure is an essential component of efficient motion planning. It follows that any humanoid robot, who wants to act efficiently in the real world, needs to be able to understand and to exploit structure.

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49

Domingues, Edgar Filipe da Silva. "Development of behaviors for humanoid robot." Master's thesis, Universidade de Aveiro, 2011. http://hdl.handle.net/10773/7429.

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Mestrado em Engenharia de Computadores e Telemática
Humanoid robotics is an area of active research. Robots with human body are better suited to execute tasks in environments designed for humans. Moreover, people feel more comfortable interacting with robots that have a human appearance. RoboCup encourages robotic research by promoting robotic competitions. One of these competitions is the Standard Platform League (SPL) in which humanoid robots play soccer. The robot used is the Nao robot, created by Aldebaran Robotics. The di erence between the teams that compete in this league is the software that controls the robots. Another league promoted by RoboCup is the 3D Soccer Simulation League (3DSSL). In this league the soccer game is played in a computer simulation. The robot model used is also the one of the Nao robot. However, there are a few di erences in the dimensions and it has one more Degree of Freedom (DoF) than the real robot. Moreover, the simulator cannot reproduce reality with precision. Both these leagues are relevant for this thesis, since they use the same robot model. The objective of this thesis is to develop behaviors for these leagues, taking advantage of the previous work developed for the 3DSSL. These behaviors include the basic movements needed to play soccer, namely: walking, kicking the ball, and getting up after a fall. This thesis presents the architecture of the agent developed for the SPL, which is similar to the architecture of the FC Portugal team agent from the 3DSSL, hence allowing to port code between both leagues easily. It was also developed an interface that allows to control a leg in a more intuitive way. It calculates the joint angles of the leg, using the following parameters: three angles between the torso and the line connecting hip and ankle; two angles between the foot and the perpendicular of the torso; and the distance between the hip and the ankle. It was also developed an algorithm to calculate the three joint angles of the hip that produce the desired vertical rotation, since the Nao robot does not have a vertical joint in the hip. This thesis presents also the behaviors developed for the SPL, some of them based on the existing behaviors from the 3DSSL. It is presented a behavior that allows to create robot movements by de ning a sequence of poses, an open-loop omnidirectional walking algorithm, and a walk optimized in the simulator adapted to the real robot. Feedback was added to this last walk to make it more robust against external disturbances. Using the behaviors presented in this thesis, the robot achieved a forward velocity of 16 cm/s, a lateral velocity of 6 cm/s, and rotated at 40 deg/s. The work developed in this thesis allows to have an agent to control the Nao robot and execute the basic low level behaviors for competing in the SPL. Moreover, the similarities between the architecture of the agent for the SPL with that of the agent from the 3DSSL allow to use the same high level behaviors in both leagues.
A robótica humanoide é uma área em ativo desenvolvimento. Os robôs com forma humana estão melhor adaptados para executarem tarefas em ambientes desenhados para humanos. Além disso, as pessoas sentem-se mais confortáveis quando interagem com robôs que tenham aparência humana. O RoboCup incentiva a investigação na área da robótica através da realização de competições de robótica. Uma destas competições é a Standard Platform League (SPL) na qual robôs humanoides jogam futebol. O robô usado é o robô Nao, criado pela Aldebaran Robotics. A diferença entre as equipas que competem nesta liga está no software que controla os robôs. Outra liga presente no RoboCup é a 3D Soccer Simulation League (3DSSL). Nesta liga o jogo de futebol é jogado numa simulação por computador. O modelo de robô usado é também o do robô Nao. Contudo, existem umas pequenas diferenças nas dimensões e este tem mais um grau de liberdade do que o robô real. O simulador também não consegue reproduzir a realidade com perfeição. Ambas estas ligas são importantes para esta dissertação, pois usam o mesmo modelo de robô. O objectivo desta dissertação é desenvolver comportamentos para estas ligas, aproveitando o trabalho prévio desenvolvido para a 3DSSL. Estes comportamentos incluem os movimentos básicos necessários para jogar futebol, nomeadamente: andar, chutar a bola e levantar-se depois de uma queda. Esta dissertação apresenta a arquitetura do agente desenvolvida para a SPL, que é similar á arquitetura do agente da equipa FC Portugal da 3DSSL, para permitir uma mais fácil partilha de código entre as ligas. Foi também desenvolvida uma interface que permite controlar uma perna de maneira mais intuitiva. Ela calcula os ângulos das juntas da perna, usando os seguintes parâmetros: três ângulos entre o torso e a linha que une anca ao tornozelo; dois ângulos entre o pé e a perpendicular do torso; e a distância entre a anca e o tornozelo. Nesta dissertação foi também desenvolvido um algoritmo para calcular os três ângulos das juntas da anca que produzam a desejada rotação vertical, visto o robô Nao não ter uma junta na anca que rode verticalmente. Esta dissertação também apresenta os comportamentos desenvolvidos para a SPL, alguns dos quais foram baseados nos comportamentos já existentes na 3DSSL. É apresentado um modelo de comportamento que permite criar movimentos para o robô de nindo uma sequência de poses, um algoritmo para um andar open-loop e omnidirecional e um andar otimizado no simulador e adaptado para o robô real. A este último andar foi adicionado um sistema de feedback para o tornar mais robusto. Usando os comportamentos apresentados nesta dissertação, o robô atingiu uma velocidade de 16 cm/s para frente, 6 cm/s para o lado e rodou sobre si pr oprio a 40 graus/s. O trabalho desenvolvido nesta dissertação permite ter um agente que controle o robô Nao e execute os comportamentos básicos de baixo nível para competir na SPL. Além disso, as semelhan cas entre a arquitetura do agente para a SPL com a arquitetura do agente da 3DSSL permite usar os mesmos comportamentos de alto nível em ambas as ligas.

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50

Akalin, Gokcan. "Simulation Of Biped Locomotion Of Humanoid Robots In 3d Space." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612470/index.pdf.

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The main goal of this thesis is to simulate the response of a humanoid robot using a specified control algorithm which can achieve a sustainable biped locomotion with 4 basic locomotion phases. Basic parts for the body of the humanoid robot model are shaped according to the specified basic physical parameters and assumed kinematic model. The kinematic model, which does not change according to locomotion phases and consists of 27 segments including 14 virtual segments, provides a humanoid robot model with 26 degrees of freedom (DOF). Corresponding kinematic relations for the robot model are obtained by recursive formulations. Derivation of dynamic equations is carried out by the Newton-Euler formulation. A trajectory definition algorithm which defines positions, orientations, translational and angular velocities for the hip and its mass center, toe part of the foot and its toe point is created. A control strategy based on predictive optimum command acceleration calculations and computed torque control method is implemented. The simulation is executed in Simulink and the visualization of the simulation is established in a virtual environment by Virtual Reality Toolbox of MATLAB. The simulation results and the user defined reference input are displayed simultaneously in the virtual environment. In this study, a simulation environment for the biped locomotion of humanoid robots is created. By the help of this thesis, the user can test various control strategies by modifying the modular structure of the simulation and acquire necessary information for the preliminary design study of a humanoid robot construction.

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Dissertations / Theses on the topic 'Humanoid Robots'

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