Готові списки джерел за темами / Hidden robot

Добірка наукової літератури з теми "Hidden robot"

Автор: Grafiati
Опубліковано: 12 червня 2021
Оновлено: 18 лютого 2022

Оформте джерело за APA, MLA, Chicago, Harvard та іншими стилями

Оберіть тип джерела:

Ознайомтеся зі списками актуальних статей, книг, дисертацій, тез та інших наукових джерел на тему "Hidden robot".

Біля кожної праці в переліку літератури доступна кнопка «Додати до бібліографії». Скористайтеся нею – і ми автоматично оформимо бібліографічне посилання на обрану працю в потрібному вам стилі цитування: APA, MLA, «Гарвард», «Чикаго», «Ванкувер» тощо.

Також ви можете завантажити повний текст наукової публікації у форматі «.pdf» та прочитати онлайн анотацію до роботи, якщо відповідні параметри наявні в метаданих.

Зміст

  1. Статті в журналах
  2. Дисертації
  3. Книги
  4. Частини книг
  5. Тези доповідей конференцій

Статті в журналах з теми "Hidden robot":

1

Nourian Zavareh, Mahdi, Fahimeh Nazarimehr, Karthikeyan Rajagopal, and Sajad Jafari. "Hidden Attractor in a Passive Motion Model of Compass-Gait Robot." International Journal of Bifurcation and Chaos 28, no. 14 (December 30, 2018): 1850171. http://dx.doi.org/10.1142/s0218127418501717.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
Many studies have been done on different aspects of biped robots such as motion, path planning, control and stability. Dynamical properties of biped robot on a sloping surface such as equilibria and their stabilities, bifurcations and basin of attraction are investigated in this paper. Basin of attraction is an important property since it can determine the unseen conditions which affect the attractor of the system with multistabilities. By the help of basin of attractions, the paper claims that the strange attractors of compass-gait robot are hidden.
2

Wu, Hongmin, Yisheng Guan, and Juan Rojas. "Analysis of multimodal Bayesian nonparametric autoregressive hidden Markov models for process monitoring in robotic contact tasks." International Journal of Advanced Robotic Systems 16, no. 2 (March 1, 2019): 172988141983484. http://dx.doi.org/10.1177/1729881419834840.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
Robot introspection aids robots to understand what they do and how they do it. Previous robot introspection techniques have often used parametric hidden Markov models or supervised learning techniques, implying that the number of hidden states or classes is defined a priori and fixed through the entire modeling process. Fixed parameterizations limit the modeling power of a process to properly encode the data. Furthermore, first-order Markov models are limited in their ability to model complex data sequences that represent highly dynamic behaviors as they assume observations are conditionally independent given the state. In this work, we contribute a Bayesian nonparametric autoregressive Hidden Markov model for the monitoring of robot contact tasks, which are characterized by complex dynamical data that are hard to model. We used a nonparametric prior that endows our hidden Markov models with an unbounded number of hidden states for a given robot skill (or subtask). We use a hierarchical Dirichlet stochastic process prior to learn an hidden Markov model with a switching vector autoregressive observation model of wrench signatures and end-effector pose for the manipulation contact tasks. The proposed scheme monitors both nominal skill execution and anomalous behaviors. Two contact tasks are used to measure the effectiveness of our approach: (i) a traditional pick-and-place task composed of four skills and (ii) a cantilever snap assembly task (also composed of four skills). The modeling performance or our approach was compared with other methods, and classification accuracy measures were computed for skill and anomaly identification. The hierarchical Dirichlet stochastic process prior to learn an hidden Markov model with a switching vector autoregressive observation model was shown to have excellent process monitoring performance with higher identification rates and monitoring ability.
3

Chen, Tianyan, Jinsong Lin, Deyu Wu, and Haibin Wu. "Research of Calibration Method for Industrial Robot Based on Error Model of Position." Applied Sciences 11, no. 3 (January 31, 2021): 1287. http://dx.doi.org/10.3390/app11031287.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
Based on the current situation of high precision and comparatively low APA (absolute positioning accuracy) in industrial robots, a calibration method to enhance the APA of industrial robots is proposed. In view of the "hidden" characteristics of the RBCS (robot base coordinate system) and the FCS (flange coordinate system) in the measurement process, a comparatively general measurement and calibration method of the RBCS and the FCS is proposed, and the source of the robot terminal position error is classified into three aspects: positioning error of industrial RBCS, kinematics parameter error of manipulator, and positioning error of industrial robot end FCS. The robot position error model is established, and the relation equation of the robot end position error and the industrial robot model parameter error is deduced. By solving the equation, the parameter error identification and the supplementary results are obtained, and the method of compensating the error by using the robot joint angle is realized. The Leica laser tracker is used to verify the calibration method on ABB IRB120 industrial robot. The experimental results show that the calibration method can effectively enhance the APA of the robot.
4

Kheddar, A., C. Tzafestas, and P. Coiffet. "Hidden robot concept — High level abstraction teleoperation." Computer Standards & Interfaces 20, no. 6-7 (March 1999): 433. http://dx.doi.org/10.1016/s0920-5489(99)90875-9.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Kheddar, A. "Teleoperation based on the hidden robot concept." IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 31, no. 1 (2001): 1–13. http://dx.doi.org/10.1109/3468.903862.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Fox, Maria, Malik Ghallab, Guillaume Infantes, and Derek Long. "Robot introspection through learned hidden Markov models." Artificial Intelligence 170, no. 2 (February 2006): 59–113. http://dx.doi.org/10.1016/j.artint.2005.05.007.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Savage, Jesus, Oscar Fuentes, Luis Contreras, and Marco Negrete. "Map representation using hidden markov models for mobile robot localization." MATEC Web of Conferences 161 (2018): 03011. http://dx.doi.org/10.1051/matecconf/201816103011.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
This paper describes a map representation and localization system for a mobile robot based on Hidden Markov Models. These models are used not only to find a region where a mobile robot is, but also they find the orientation that it has. It is shown that an estimation of the region where the robot is located can be found using the Viterbi algorithm with quantized laser readings, i.e. symbol observations, of a Hidden Markov Model.
8

Durdu, Akif, Aydan M. Erkmen, and Alper Yilmaz. "Reshaping human intention in Human-Robot Interactions by robot moves." Interaction Studies 20, no. 3 (November 18, 2019): 530–60. http://dx.doi.org/10.1075/is.18068.dur.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
Abstract This paper outlines the methodology and experiments associated with the reshaping of human intentions based on robot movements within Human-Robot Interactions (HRIs). Although studies on estimating human intentions are well studied in the literature, reshaping intentions through robot-initiated interactions is a new significant branching in the field of HRI. In this paper, we analyze how estimated human intentions can intentionally change through cooperation with mobile robots in real Human-Robot environments. This paper proposes an intention-reshaping system that includes either the Observable Operator Models (OOMs) or Hidden Markov Models (HMMs) to estimate human intention and decide which moves a robot should perform to reshape previously estimated human intentions into desired ones. At the low level, the system needs to track the locations of all mobile agents using cameras. We test our system on videos taken in a real HRI environment that has been developed as our experimental setup. The results show that OOMs are faster than HMMs and both models give correct decisions for testing sequences.
9

Murao, Hajime, and Shinzo Kitamura. "Building up Embodiment in Learning Agents Using A Gaussian Radial Basis Function Neural Network." Journal of Robotics and Mechatronics 12, no. 6 (December 20, 2000): 656–63. http://dx.doi.org/10.20965/jrm.2000.p0656.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
In this paper, we propose actor-critic learning with adaptive state space construction. The gaussian radial basis function neural network is employed for both the actor and the critic modules, where each hidden neuron covers a subspace of the sensor space and so the hidden layer corresponds to the state space. In the proposed algorithm, a robot starts without any states and a new state is generated incrementally by adding a new hidden neuron. One clear advantage of the proposed algorithm to others is the performance improvement by the minimal training after adding a new state, i.e. the adjustment of the connective strength between the new neuron and others is only required after adding a new hidden neuron. This provides an efficient method to construct the state space during the learning in the real world. Resulting state space represents aspects of the environment in which the robot works and the characteristic of the robot itself. In this sense, the obtained state space is said to represent the embodiment of the robot.
10

ALNAJJAR, FADY, and KAZUYUKI MURASE. "SELF-ORGANIZATION OF SPIKING NEURAL NETWORK THAT GENERATES AUTONOMOUS BEHAVIOR IN A REAL MOBILE ROBOT." International Journal of Neural Systems 16, no. 04 (August 2006): 229–39. http://dx.doi.org/10.1142/s0129065706000640.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
In this paper, we propose self-organization algorithm of spiking neural network (SNN) applicable to autonomous robot for generation of adoptive and goal-directed behavior. First, we formulated a SNN model whose inputs and outputs were analog and the hidden unites are interconnected each other. Next, we implemented it into a miniature mobile robot Khepera. In order to see whether or not a solution(s) for the given task(s) exists with the SNN, the robot was evolved with the genetic algorithm in the environment. The robot acquired the obstacle avoidance and navigation task successfully, exhibiting the presence of the solution. After that, a self-organization algorithm based on a use-dependent synaptic potentiation and depotentiation at synapses of input layer to hidden layer and of hidden layer to output layer was formulated and implemented into the robot. In the environment, the robot incrementally organized the network and the given tasks were successfully performed. The time needed to acquire the desired adoptive and goal-directed behavior using the proposed self-organization method was much less than that with the genetic evolution, approximately one fifth.
Більше джерел
Також вас можуть зацікавити розширені добірки на тему "Hidden robot" для конкретних типів джерел:
Статті в журналах

Дисертації з теми "Hidden robot":

1

Reynaga, Barba Valeria. "Detecting Changes During the Manipulation of an Object Jointly Held by Humans and RobotsDetektera skillnader under manipulationen av ett objekt som gemensamt hålls av människor och robotar." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-174027.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
In the last decades research and development in the field of robotics has grown rapidly. This growth has resulted in the emergence of service robots that need to be able to physically interact with humans for different applications. One of these applications involves robots and humans cooperating in handling an object together. In such cases, there is usually an initial arrangement of how the robot and the humans hold the object and the arrangement stays the same throughout the manipulation task. Real-world scenarios often require that the initial arrangement changes throughout the task, therefore, it is important that the robot is able to recognize these changes and act accordingly. We consider a setting where a robot holds a large flat object with one or two humans. The aim of this research project is to detect the change in the number of agents grasping the object using only force and torque information measured at the robot's wrist. The proposed solution involves defining a transition sequence of four steps that the humans should perform to go from the initial scenario to the final one. The force and torque information is used to estimate the grasping point of the agents with a Kalman filter. While the humans are going from one scenario to the other, the estimated point changes according to the step of the transition the humans are in. These changes are used to track the steps in the sequence using a hidden Markov model (HMM). Tracking the steps in the sequence means knowing how many agents are grasping the object. To evaluate the method, humans that were not involved in the training of the HMM were asked to perform two tasks: a) perform the previously defined sequence as is, and b) perform a deviation of the sequence. The results of the method show that it is possible to detect the change between one human and two humans holding the object using only force and torque information.
2

Seyhan, Seyit Sabri. "Simple And Complex Behavior Learning Using Behavior Hidden Markov Model And Cobart." Phd thesis, METU, 2013. http://etd.lib.metu.edu.tr/upload/12615508/index.pdf.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
In this thesis, behavior learning and generation models are proposed for simple and complex behaviors of robots using unsupervised learning methods. Simple behaviors are modeled by simple-behavior learning model (SBLM) and complex behaviors are modeled by complex-behavior learning model (CBLM) which uses previously learned simple or complex behaviors. Both models have common phases named behavior categorization, behavior modeling, and behavior generation. Sensory data are categorized using correlation based adaptive resonance theory network that generates motion primitives corresponding to robot'
s base abilities in the categorization phase. In the modeling phase, Behavior-HMM, a modified version of hidden Markov model, is used to model the relationships among the motion primitives in a finite state stochastic network. In addition, a motion generator which is an artificial neural network is trained for each motion primitive to learn essential robot motor commands. In the generation phase, desired task is presented as a target observation and the model generates corresponding motion primitive sequence. Then, these motion primitives are executed successively by the motion generators which are specifically trained for the corresponding motion primitives. The models are not proposed for one specific behavior, but are intended to be bases for all behaviors. CBLM enhances learning capabilities by integrating previously learned behaviors hierarchically. Hence, new behaviors can take advantage of already discovered behaviors. The proposed models are tested on a robot simulator and the experiments showed that simple and complex-behavior learning models can generate requested behaviors effectively.
3

Zhu, Minglei. "Control-based design of Robots." Thesis, Ecole centrale de Nantes, 2020. http://www.theses.fr/2020ECDN0043.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
Il est bien connu que les robots parallèles ont de nombreuses applications dans l ’industrie. Cependant, en raison de leur structure complexe, leur contrôle peut être difficile. Lorsqu'une précision élevée est nécessaire , un modèle complet du robot détaillé est nécessaire . Les approches de contrôle référencées capteurs se sont avérées plus efficaces , en termes de précision que les contrôleurs basés modèles puisqu'elles s’affranchissent des modèles de robots complexes et des erreurs de modélisation associées. Néanmoins, lors de l'application de d’un asservissement visuel , il y a toujours des problèmes dans le processus de contrôle , tels que les singularités du contrôleur . Cette thèse propose une méthodologie de conception orientée commande qui prend en compte les performances de précision du contrôleur dans le processus de conception du robot pour obtenir les paramètres géométriques optimaux de ce dernier Trois contrôleurs ont été sélectionnés dans le processus de conception du robot : les commandes basées sur l’observation des directions des jambes, les commandes basées sur l’observation des lignes et les commandes basées sur des moments dans l'image .Pour vérifier les performances en terme de précision des robots optimisés, nous avons effectué des co-simulations des robots optimisés avec les contrôleurs correspondants . En terme d’expérimentation, deux prototypes de robots DELTA ont été conçus et expérimentés afin de valider la précision du contrôleur
It is well -known that parallel robots have a lot of applications in industry for their high stiffness , high payload , can reach higher acceleration and speed . However , because of their complex structure , their control may be troublesome. When high accuracy is needed, the detailed robot model is necessary . However , even detailed models still suffer from the problem of inaccuracy in reality because of robot assembly and manufacturing errors . Sensor - based control approaches have been proven to be more efficient than model-based controllers in terms of accuracy since they overcome the complex robot models and inconsistency errors. Nevertheless, when applying the visual servoing, there are always some problems in the control process , such as the controller singularities . Thus , this thesis proposes proposes a control based design metodology which takes into account the accuracy performance of the controller in the design process to get the geometric parameters of the robot. This thesis applied the control-based design methodology to the optimal design of three types of parallel robots: Five-bar mechanisms , DELTA robots , Gough -Stewart platforms . Three types of controllers are selected in the design process : leg -direction -based visual servoing, line-baesd visual servoing and image moment visual servoing . Design optimization problems are formulated to find the geometric parameters of the robot . Co-simulations are performed to check the accuracy performance of the robots obtained from the optimization. Experiments are performed with two DELTA robot prototypes in order to validate the controller accuracy
4

Khokar, Karan Hariharan. "Human Intention Recognition Based Assisted Telerobotic Grasping of Objects in an Unstructured Environment." Scholar Commons, 2013. http://scholarcommons.usf.edu/etd/4909.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
In this dissertation work, a methodology is proposed to enable a robot to identify an object to be grasped and its intended grasp configuration while a human is teleoperating a robot towards the desired object. Based on the detected object and grasp configuration, the human is assisted in the teleoperation task. The environment is unstructured and consists of a number of objects, each with various possible grasp configurations. The identification of the object and the grasp configuration is carried out in real time, by recognizing the intention of the human motion. Simultaneously, the human user is assisted to preshape over the desired grasp configuration. This is done by scaling the components of the remote arm end-effector motion that lead to the desired grasp configuration and simultaneously attenuating the components that are in perpendicular directions. The complete process occurs while manipulating the master device and without having to interact with another interface. Intention recognition from motion is carried out by using Hidden Markov Model (HMM) theory. First, the objects are classified based on their shapes. Then, the grasp configurations are preselected for each object class. The selection of grasp configurations is based on the human knowledge of robust grasps for the various shapes. Next, an HMM for each object class is trained by having a skilled teleoperator perform repeated preshape trials over each grasp configuration of the object class in consideration. The grasp configurations are modeled as the states of each HMM whereas the projections of translation and orientation vectors, over each reference vector, are modeled as observations. The reference vectors are the ideal translation and rotation trajectories that lead the remote arm end-effector towards a grasp configuration. During an actual grasping task performed by a novice or a skilled user, the trained model is used to detect their intention. The output probability of the HMM associated with each object in the environment is computed as the user is teleoperating towards the desired object. The object that is associated with the HMM which has the highest output probability, is taken as the desired object. The most likely Viterbi state sequence of the selected HMM gives the desired grasp configuration. Since an HMM is associated with every object, objects can be shuffled around, added or removed from the environment without the need to retrain the models. In other words, the HMM for each object class needs to be trained only once by a skilled teleoperator. The intention recognition algorithm was validated by having novice users, as well as the skilled teleoperator, grasp objects with different grasp configurations from a dishwasher rack. Each object had various possible grasp configurations. The proposed algorithm was able to successfully detect the operator's intention and identify the object and the grasp configuration of interest. This methodology of grasping was also compared with unassisted mode and maximum-projection mode. In the unassisted mode, the operator teleoperated the arm without any assistance or intention recognition. In the maximum-projection mode, the maximum projection of the motion vectors was used to determine the intended object and the grasp configuration of interest. Six healthy and one wheelchair-bound individuals, each executed twelve pick-and-place trials in intention-based assisted mode and unassisted mode. In these trials, they picked up utensils from the dishwasher and laid them on a table located next to it. The relative positions and orientations of the utensils were changed at the end of every third trial. It was observed that the subjects were able to pick-and-place the objects 51% faster and with less number of movements, using the proposed method compared to the unassisted method. They found it much easier to execute the task using the proposed method and experienced less mental and overall workloads. Two able-bodied subjects also executed three preshape trials over three objects in intention-based assisted and maximum projection mode. For one of the subjects, the objects were shuffled at the end of the six trials and she was asked to carry out three more preshape trials in the two modes. This time, however, the subject was made to change their intention when she was about to preshape to the grasp configurations. It was observed that intention recognition was consistently accurate through the trajectory in the intention-based assisted method except at a few points. However, in the maximum-projection method the intention recognition was consistently inaccurate and fluctuated. This often caused to subject to be assisted in the wring directions and led to extreme frustration. The intention-based assisted method was faster and had less hand movements. The accuracy of the intention based method did not change when the objects were shuffled. It was also shown that the model for intention recognition can be trained by a skilled teleoperator and be used by a novice user to efficiently execute a grasping task in teleoperation.
5

Wåhlin, Peter. "Enhanching the Human-Team Awareness of a Robot." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-16371.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
The use of autonomous robots in our society is increasing every day and a robot is no longer seen as a tool but as a team member. The robots are now working side by side with us and provide assistance during dangerous operations where humans otherwise are at risk. This development has in turn increased the need of robots with more human-awareness. Therefore, this master thesis aims at contributing to the enhancement of human-aware robotics. Specifically, we are investigating the possibilities of equipping autonomous robots with the capability of assessing and detecting activities in human teams. This capability could, for instance, be used in the robot's reasoning and planning components to create better plans that ultimately would result in improved human-robot teamwork performance. we propose to improve existing teamwork activity recognizers by adding intangible features, such as stress, motivation and focus, originating from human behavior models. Hidden markov models have earlier been proven very efficient for activity recognition and have therefore been utilized in this work as a method for classification of behaviors. In order for a robot to provide effective assistance to a human team it must not only consider spatio-temporal parameters for team members but also the psychological.To assess psychological parameters this master thesis suggests to use the body signals of team members. Body signals such as heart rate and skin conductance. Combined with the body signals we investigate the possibility of using System Dynamics models to interpret the current psychological states of the human team members, thus enhancing the human-awareness of a robot.
Användningen av autonoma robotar i vårt samhälle ökar varje dag och en robot ses inte längre som ett verktyg utan som en gruppmedlem. Robotarna arbetar nu sida vid sida med oss och ger oss stöd under farliga arbeten där människor annars är utsatta för risker. Denna utveckling har i sin tur ökat behovet av robotar med mer människo-medvetenhet. Därför är målet med detta examensarbete att bidra till en stärkt människo-medvetenhet hos robotar. Specifikt undersöker vi möjligheterna att utrusta autonoma robotar med förmågan att bedöma och upptäcka olika beteenden hos mänskliga lag. Denna förmåga skulle till exempel kunna användas i robotens resonemang och planering för att ta beslut och i sin tur förbättra samarbetet mellan människa och robot. Vi föreslår att förbättra befintliga aktivitetsidentifierare genom att tillföra förmågan att tolka immateriella beteenden hos människan, såsom stress, motivation och fokus. Att kunna urskilja lagaktiviteter inom ett mänskligt lag är grundläggande för en robot som ska vara till stöd för laget. Dolda markovmodeller har tidigare visat sig vara mycket effektiva för just aktivitetsidentifiering och har därför använts i detta arbete. För att en robot ska kunna ha möjlighet att ge ett effektivt stöd till ett mänskligtlag måste den inte bara ta hänsyn till rumsliga parametrar hos lagmedlemmarna utan även de psykologiska. För att tyda psykologiska parametrar hos människor förespråkar denna masteravhandling utnyttjandet av mänskliga kroppssignaler. Signaler så som hjärtfrekvens och hudkonduktans. Kombinerat med kroppenssignalerar påvisar vi möjligheten att använda systemdynamiksmodeller för att tolka immateriella beteenden, vilket i sin tur kan stärka människo-medvetenheten hos en robot.

The thesis work was conducted in Stockholm, Kista at the department of Informatics and Aero System at Swedish Defence Research Agency.

6

Dib, Abdallah. "Vers un système de capture du mouvement humain en 3D pour un robot mobile évoluant dans un environnement encombré." Thesis, Université de Lorraine, 2016. http://www.theses.fr/2016LORR0045/document.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
Dans cette thèse nous intéressons à la conception d'un robot mobile capable d’analyser le comportement et le mouvement d’une personne en environnement intérieur et encombré, par exemple le domicile d’une personne âgée. Plus précisément, notre objectif est de doter le robot des capacités de perception visuelle de la posture humaine de façon à mieux maîtriser certaines situations qui nécessitent de comprendre l’intention des personnes avec lesquelles le robot interagit, ou encore de détecter des situations à risques comme les chutes ou encore d’analyser les capacités motrices des personnes dont il a la garde. Le suivi de la posture dans un environnement dynamique et encombré relève plusieurs défis notamment l'apprentissage en continue du fond de la scène et l'extraction la silhouette qui peut être partiellement observable lorsque la personne est dans des endroits occultés. Ces difficultés rendent le suivi de la posture une tâche difficile. La majorité des méthodes existantes, supposent que la scène est statique et la personne est toujours visible en entier. Ces approches ne sont pas adaptées pour fonctionner dans des conditions réelles. Nous proposons, dans cette thèse, un nouveau système de suivi capable de suivre la posture de la personne dans ces conditions réelles. Notre approche utilise une grille d'occupation avec un modèle de Markov caché pour apprendre en continu l'évolution de la scène et d'extraire la silhouette, ensuite un algorithme de filtrage particulaire hiérarchique est utilisé pour reconstruire la posture. Nous proposons aussi un nouvel algorithme de gestion d'occlusion capable d'identifier et d'exclure les parties du corps cachées du processus de l'estimation de la pose. Finalement, nous avons proposé une base de données contenant des images RGB-D avec la vérité-terrain dans le but d'établir une nouvelle référence pour l'évaluation des systèmes de capture de mouvement dans un environnement réel avec occlusions. La vérité-terrain est obtenue à partir d'un système de capture de mouvement à base de marqueur de haute précision avec huit caméras infrarouges. L'ensemble des données est disponible en ligne. La deuxième contribution de cette thèse, est le développement d'une méthode de localisation visuelle à partir d'une caméra du type RGB-D montée sur un robot qui se déplace dans un environnement dynamique. En effet, le système de capture de mouvement que nous avons développé doit équiper un robot se déplaçant dans une scène. Ainsi, l'estimation de mouvement du robot est importante pour garantir une extraction de silhouette correcte pour le suivi. La difficulté majeure de la localisation d'une caméra dans un environnement dynamique, est que les objets mobiles de la scène induisent un mouvement supplémentaire qui génère des pixels aberrants. Ces pixels doivent être exclus du processus de l'estimation du mouvement de la caméra. Nous proposons ainsi une extension de la méthode de localisation dense basée sur le flux optique pour isoler les pixels aberrants en utilisant l'algorithme de RANSAC
In this thesis we are interested in designing a mobile robot able to analyze the behavior and movement of a a person in indoor and cluttered environment. Our goal is to equip the robot by visual perception capabilities of the human posture to better analyze situations that require understanding of person with which the robot interacts, or detect risk situations such as falls or analyze motor skills of the person. Motion capture in a dynamic and crowded environment raises multiple challenges such as learning the background of the environment and extracting the silhouette that can be partially observable when the person is in hidden places. These difficulties make motion capture difficult. Most of existing methods assume that the scene is static and the person is always fully visible by the camera. These approaches are not able to work in such realistic conditions. In this thesis, We propose a new motion capture system capable of tracking a person in realistic world conditions. Our approach uses a 3D occupancy grid with a hidden Markov model to continuously learn the changing background of the scene and to extract silhouette of the person, then a hierarchical particle filtering algorithm is used to reconstruct the posture. We propose a novel occlusion management algorithm able to identify and discards hidden body parts of the person from process of the pose estimation. We also proposed a new database containing RGBD images with ground truth data in order to establish a new benchmark for the assessment of motion capture systems in a real environment with occlusions. The ground truth is obtained from a motion capture system based on high-precision marker with eight infrared cameras. All data is available online. The second contribution of this thesis is the development of a new visual odometry method to localize an RGB-D camera mounted on a robot moving in a dynamic environment. The major difficulty of the localization in a dynamic environment, is that mobile objects in the scene induce additional movement that generates outliers pixels. These pixels should be excluded from the camera motion estimation process in order to produce accurate and precise localization. We thus propose an extension of the dense localization method based on the optical flow method to remove outliers pixels using the RANSAC algorithm
7

Alves, Roberson Junior Fernandes. "RASTREAMENTO DE AGROBOTS EM ESTUFAS AGRÍCOLAS USANDO MODELOS OCULTOS DE MARKOV: Comparação do desempenho e da correção dos algoritmos de Viterbi e Viterbi com janela de observações deslizante." UNIVERSIDADE ESTADUAL DE PONTA GROSSA, 2015. http://tede2.uepg.br/jspui/handle/prefix/132.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
Made available in DSpace on 2017-07-21T14:19:26Z (GMT). No. of bitstreams: 1 Roberson Junior Fernandes Alves.pdf: 17901245 bytes, checksum: 170e17bbccf0e54fa9b0dab204aca2e4 (MD5) Previous issue date: 2015-09-17
Developing mobile and autonomous agrobots for greenhouses requires the use of procedures which allow robot autolocalization and tracking. The tracking problem can be modeled as finding the most likely sequence of states in a hidden Markov model„ whose states indicate the positions of an occupancy grid. This sequence can be estimated with Viterbi’s algorithm. However, the processing time and consumed memory, of this algorithm, grows with the dimensions of the grid and tracking duration, and, this can constraint its use for tracking agrobots. Considering it, this work presents a tracking procedure which uses two approximated implementations of Viterbi’s algorithm called Viterbi-JD(Viterbi’s algorithm with a sliding window) and Viterbi-JD-MTE(Viterbi’s algorithm with a sliding window over an hidden Markov model with sparse transition matrix). The experimental results show that the time and memory performance of tracking with this two approximated implementations are significantly higher than the Viterbi’s based tracking. The reported tracking hypothesis is suboptimal, when compared to the hypothesis generated by Viterbi, but the error does not grows substantially. Th experimentos was performed using RSSI(Received Signal Strength Indicator) simulated data.
O desenvolvimento de agrobots móveis e autônomos para operar em estufas agrícolas depende da implementação de procedimentos que permitam o rastreamento do robô no ambiente. O problema do rastreamento pode ser modelado como a determinação da sequência de estados mais prováveis de um modelo oculto de Markov cujos estados indicam posições de uma grade de ocupação. Esta sequência pode ser estimada pelo algoritmo de Viterbi. No entanto, o tempo de processamento e a memória consumida, por esse algoritmo, crescem com as dimensões da grade e com a duração do rastreamento, e isto pode limitar seu uso no rastreamento de agrobots em estufas. Considerando o exposto, este trabalho apresenta um procedimento de rastreamento que utiliza mplementações aproximadas do algoritmo de Viterbi denominadas de Viterbi-JD(Viterbi com janela deslizante) e Viterbi- JD-MTE(Viterbi com janela deslizante sobre um modelo oculto de Markov com matriz de transição esparsa). Os experimentos mostram que o desempenho de tempo e memória do rastreamento baseado nessas implementações aproximadas é significativamente melhor que aquele do algoritmo original. A hipótese de rastreamento gerada é sub ótima em relação àquela calculada pelo algoritmo original, contudo, não há um aumento substancial do erro. Os experimentos foram realizados utilizando dados simulados de RSSI (Received Signal Strength Indicator).
8

Blume-Werry, Gesche. "The hidden life of plants : fine root dynamics in northern ecosystems." Doctoral thesis, Umeå universitet, Institutionen för ekologi, miljö och geovetenskap, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-124757.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
Fine roots constitute a large part of the primary production in northern (arctic and boreal) ecosystems, and are key players in ecosystem fluxes of water, nutrients and carbon. Data on root dynamics are generally rare, especially so in northern ecosystems. However, those ecosystems undergo the most rapid climatic changes on the planet and a profound understanding of form, function and dynamics of roots in such ecosystems is essential. This thesis aimed to advance our knowledge about fine root dynamics in northern ecosystems, with a focus on fine root phenology in natural plant communities and how climate change might alter it. Factors considered included thickness and duration of snow cover, thawing of permafrost, as well as natural gradients in temperature. Experiments and observational studies were located around Abisko (68°21' N, 18°45' E), and in a boreal forest close to Vindeln (64°14'N, 19°46'E), northern Sweden. Root responses included root growth, total root length, and root litter input, always involving seasonal changes therein, measured with minirhizotrons. Root biomass was also determined with destructive soil sampling. Additionally, aboveground response parameters, such as phenology and growth, and environmental parameters, such as air and soil temperatures, were assessed. This thesis reveals that aboveground patterns or responses cannot be directly translated belowground and urges a decoupling of above- and belowground phenology in terrestrial biosphere models. Specifically, root growth occurred outside of the photosynthetically active period of tundra plants. Moreover, patterns observed in arctic and boreal ecosystems diverged from those of temperate systems, and models including root parameters may thus need specific parameterization for northern ecosystems. In addition, this thesis showed that plant communities differ in root properties, and that changes in plant community compositions can thus induce changes in root dynamics and functioning. This underlines the importance of a thorough understanding of root dynamics in different plant community types in order to understand and predict how changes in plant communities in response to climate change will translate into root dynamics. Overall, this thesis describes root dynamics in response to a variety of factors, because a deeper knowledge about root dynamics will enable a better understanding of ecosystem processes, as well as improve model prediction of how northern ecosystems will respond to climate change.
9

Ngan, Choi-chik, and 顔才績. "A hidden Markov model approach to force-based contact recognition for intelligent robotic assembly." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2002. http://hub.hku.hk/bib/B31243496.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Wang, Ming [Verfasser], Ian T. [Gutachter] Baldwin, Ralf [Gutachter] Oelmüller, and Le [Gutachter] Kang. "A hidden mystery : root adaptive responses to environmental factors in Nicotiana attenuata / Ming Wang ; Gutachter: Ian T. Baldwin, Ralf Oelmüller, Le Kang." Jena : Friedrich-Schiller-Universität Jena, 2018. http://d-nb.info/1205885153/34.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.

Книги з теми "Hidden robot":

1

Meinig, George. Root canal cover-up exposed!: Many illness result : dentist to the stars discovers hidden truth-- tells what to do. Ojai, Calif: Bion Pub., 1993.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Whitney, R. D. The hidden enemy: Root rot technology transfer ; for practical use in the field : a forester's guide to identification and reduction of major root rots in Ontario. [Ottawa, Ont.]: Minister of Supply and Services Canada, 1988.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Schwartz, Steven A. The Big Book of Nintendo Games. Greensboro, USA: Compute Books, 1991.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Fung, Jason, and Benjamin Bikman. Why We Get Sick: The Hidden Epidemic at the Root of Most Chronic Disease―and How to Fight It. BenBella Books, 2020.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Bikman, Benjamin. Why We Get Sick: The Hidden Epidemic at the Root of Most Chronic Disease--and How to Fight It. Blackstone Publishing, 2020.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Bikman, Benjamin. Why We Get Sick: The Hidden Epidemic at the Root of Most Chronic Disease--and How to Fight It. Blackstone Publishing, 2020.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Bikman, Benjamin. Why We Get Sick: The Hidden Epidemic at the Root of Most Chronic Disease and How to Fight It. BenBella Books, 2021.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Moritz, Andreas. Cancer Is Not a Disease!: It's a Healing Mechanism; Discover Cancer's Hidden Purpose, Heal Its Root Causes, and Be Healthier Than Ever. Blackstone Audio, Inc., 2012.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Heiner, Prof, Bielefeldt, Ghanea Nazila, Dr, and Wiener Michael, Dr. Part 2 Discrimination, 2.1 Discrimination on the Basis of Religion or Belief/Interreligious Discrimination/Tolerance. Oxford University Press, 2016. http://dx.doi.org/10.1093/law/9780198703983.003.0017.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
This chapter focuses on religious discrimination. Not only does freedom of religion or belief prohibit undue infringements into a person’s religious freedom; it also prohibits discrimination—the denial of equality and unfair treatment based on religion. The discussion on discrimination has become more and more complex in recent debate, both with a view to different types of actors (State institutions, de facto authorities, and non-State institutions) and to different forms of discrimination (direct, indirect, structural, intersectional). While many experiences of discrimination continue to be overt and recognizable, more sensitivity has also arisen concerning concealed forms of discrimination, such as indirect discrimination, sometimes hidden under seemingly neutral rules. Reasonable accommodation should be used to tackle these phenomena. Moreover the State bears the responsibility to address the root causes of intolerance, societal discrimination, and violence committed in the name of religion.
10

Liang, Xiaodon. Curbing Illicit Financial Flows. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198805373.003.0013.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
Illicit financial flows (IFFs) drain state finances and economic vitality, with disproportionate impact on developing economies. IFFs—including money laundering, tax evasion, and tax avoidance—pose a transnational problem addressed so far through international regimes of coordination and cooperation. But meaningful reductions in IFFs require addressing the root of the problem: information asymmetries. Developed nations and tax havens know where money is hidden and profits are made, while developing nations do not. Since the international system of global finance creates the incentive structure and permissive environment for illicit flows, it is at this level that states must focus their policy-making attention. New information-sharing mechanisms, such as automatic exchange of tax information and public country-by-country tax reporting, can level the playing field and enable lower-income states to effectively address the IFF problem.

Частини книг з теми "Hidden robot":

1

Coste, Michel, Philippe Wenger, and Damien Chablat. "Hidden Cusps." In Advances in Robot Kinematics 2016, 129–38. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56802-7_14.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

García-Álvarez, Francisco Manuel, and Matilde Santos. "Educational-Oriented Mobile Robot: Hidden Lessons." In Advances in Intelligent Systems and Computing, 61–71. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-57799-5_7.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Noda, Itsuki. "Hidden Markov Modeling of Team-Play Synchronization." In RoboCup 2003: Robot Soccer World Cup VII, 102–13. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25940-4_9.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Briot, Sébastien, Victor Rosenzveig, and Philippe Martinet. "The Hidden Robot Concept: A Tool for Control Analysis and Robot Control-Based Design." In Advances in Robot Kinematics, 31–39. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06698-1_4.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Boudnaya, Jaouad, Amine Haytoumi, Omar Eddayer, and Abdelhak Mkhida. "Prediction of Robot Localization States Using Hidden Markov Models." In Advances in Intelligent Systems and Computing, 253–62. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51186-9_18.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Noda, Itsuki. "Hidden Markov Modeling of Multi-agent Systems and Its Learning Method." In RoboCup 2002: Robot Soccer World Cup VI, 94–110. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-45135-8_8.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Tanwani, Ajay Kumar, Jonathan Lee, Brijen Thananjeyan, Michael Laskey, Sanjay Krishnan, Roy Fox, Ken Goldberg, and Sylvain Calinon. "Generalizing Robot Imitation Learning with Invariant Hidden Semi-Markov Models." In Springer Proceedings in Advanced Robotics, 196–211. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44051-0_12.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Lochan, Kshetrimayum, Jay Prakash Singh, Binoy Krishna Roy, and Bidyadhar Subudhi. "Hidden Chaotic Path Planning and Control of a Two-Link Flexible Robot Manipulator." In Nonlinear Dynamical Systems with Self-Excited and Hidden Attractors, 433–63. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-71243-7_19.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Pinheiro, Paulo Gurgel, Josue J. G. Ramos, Vander L. Donizete, Pedro Picanço, and Gustavo H. De Oliveira. "Workplace Emotion Monitoring—An Emotion-Oriented System Hidden Behind a Receptionist Robot." In Mechatronics and Robotics Engineering for Advanced and Intelligent Manufacturing, 407–20. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33581-0_32.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Balali, Sogol, Ross T. Sowell, William D. Smart, and Cindy M. Grimm. "Privacy Concerns in Robot Teleoperation: Does Personality Influence What Should Be Hidden?" In Social Robotics, 719–29. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-35888-4_67.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.

Тези доповідей конференцій з теми "Hidden robot":

1

Ferguson, D., A. Stentz, and S. Thrun. "PAO for planning with hidden state." In IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004. IEEE, 2004. http://dx.doi.org/10.1109/robot.2004.1307491.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Shepherd, David C., Nicholas A. Kraft, and Patrick Francis. "Visualizing the "Hidden" Variables in Robot Programs." In 2019 IEEE/ACM 2nd International Workshop on Robotics Software Engineering (RoSE). IEEE, 2019. http://dx.doi.org/10.1109/rose.2019.00007.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Jingjin Yu and Steven M. LaValle. "Tracking hidden agents through shadow information spaces." In 2008 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2008. http://dx.doi.org/10.1109/robot.2008.4543562.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Lu, Wei-zhou, and Shun-zheng Yu. "Web Robot Detection Based on Hidden Markov Model." In 2006 International Conference on Communications, Circuits and Systems. IEEE, 2006. http://dx.doi.org/10.1109/icccas.2006.285024.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Thorniley, James, and Phil Husbands. "Hidden information transfer in an autonomous swinging robot." In European Conference on Artificial Life 2013. MIT Press, 2013. http://dx.doi.org/10.7551/978-0-262-31709-2-ch074.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Dongheui Lee, Dana Kulic, and Yoshihiko Nakamura. "Missing motion data recovery using factorial hidden Markov models." In 2008 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2008. http://dx.doi.org/10.1109/robot.2008.4543449.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Kulic, Dana, and Elizabeth Croft. "Estimating Robot Induced Affective State using Hidden Markov Models." In ROMAN 2006 - The 15th IEEE International Symposium on Robot and Human Interactive Communication. IEEE, 2006. http://dx.doi.org/10.1109/roman.2006.314427.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Miller, Nicholas, Mohan A. Thomas, Justin A. Eichel, and Akshaya Mishra. "A Hidden Markov Model for Vehicle Detection and Counting." In 2015 12th Conference on Computer and Robot Vision (CRV). IEEE, 2015. http://dx.doi.org/10.1109/crv.2015.42.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Wu, Hongmin, Hongbin Lin, Yisheng Guan, Kensuke Harada, and Juan Rojas. "Robot introspection with Bayesian nonparametric vector autoregressive hidden Markov models." In 2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids). IEEE, 2017. http://dx.doi.org/10.1109/humanoids.2017.8246976.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Sarmiento, Carlos, Jesus Savage, Alfredo Juarez, Luis Contreras, Abel Pacheco, and Mauricio Matamoros. "Feature detection using Hidden Markov Models for 3D-visual recognition." In 2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC). IEEE, 2019. http://dx.doi.org/10.1109/icarsc.2019.8733651.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.

До бібліографії