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Kruse, Thibault. "Planning for human robot interaction." Thesis, Toulouse 3, 2015. http://www.theses.fr/2015TOU30059/document.
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Les avancées récentes en robotique inspirent des visions de robots domestiques et de service rendant nos vies plus faciles et plus confortables. De tels robots pourront exécuter différentes tâches de manipulation d'objets nécessaires pour des travaux de ménage, de façon autonome ou en coopération avec des humains. Dans ce rôle de compagnon humain, le robot doit répondre à de nombreuses exigences additionnelles comparées aux domaines bien établis de la robotique industrielle. Le but de la planification pour les robots est de parvenir à élaborer un comportement visant à satisfaire un but et qui obtient des résultats désirés et dans de bonnes conditions d'efficacité. Mais dans l'interaction homme-robot (HRI), le comportement robot ne peut pas simplement être jugé en termes de résultats corrects, mais il doit être agréable aux acteurs humains. Cela signifie que le comportement du robot doit obéir à des critères de qualité supplémentaire. Il doit être sûr, confortable pour l'homme, et être intuitivement compris. Il existe des pratiques pour assurer la sécurité et offrir un confort en gardant des distances suffisantes entre le robot et des personnes à proximité. Toutefois fournir un comportement qui est intuitivement compris reste un défi. Ce défi augmente considérablement dans les situations d'interaction homme-robot dynamique, où les actions de la personne sont imprévisibles, le robot devant adapter en permanence ses plans aux changements. Cette thèse propose une approche nouvelle et des méthodes pour améliorer la lisibilité du comportement du robot dans des situations dynamiques. Cette approche ne considère pas seulement la qualité d'un seul plan, mais le comportement du robot qui est parfois le résultat de replanifications répétées au cours d'une interaction. Pour ce qui concerne les tâches de navigation, cette thèse présente des fonctions de coûts directionnels qui évitent les problèmes dans des situations de conflit. Pour la planification d'action en général, cette thèse propose une approche de replanification locale des actions de transport basé sur les coûts de navigation, pour élaborer un comportement opportuniste adaptatif. Les deux approches, complémentaires, facilitent la compréhension, par les acteurs et observateurs humains, des intentions du robot et permettent de réduire leur confusionThe recent advances in robotics inspire visions of household and service robots making our lives easier and more comfortable. Such robots will be able to perform several object manipulation tasks required for household chores, autonomously or in cooperation with humans. In that role of human companion, the robot has to satisfy many additional requirements compared to well established fields of industrial robotics. The purpose of planning for robots is to achieve robot behavior that is goal-directed and establishes correct results. But in human-robot-interaction, robot behavior cannot merely be judged in terms of correct results, but must be agree-able to human stakeholders. This means that the robot behavior must suffice additional quality criteria. It must be safe, comfortable to human, and intuitively be understood. There are established practices to ensure safety and provide comfort by keeping sufficient distances between the robot and nearby persons. However providing behavior that is intuitively understood remains a challenge. This challenge greatly increases in cases of dynamic human-robot interactions, where the actions of the human in the future are unpredictable, and the robot needs to constantly adapt its plans to changes. This thesis provides novel approaches to improve the legibility of robot behavior in such dynamic situations. Key to that approach is not to merely consider the quality of a single plan, but the behavior of the robot as a result of replanning multiple times during an interaction. For navigation planning, this thesis introduces directional cost functions that avoid problems in conflict situations. For action planning, this thesis provides the approach of local replanning of transport actions based on navigational costs, to provide opportunistic behavior. Both measures help human observers understand the robot's beliefs and intentions during interactions and reduce confusion
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Switzer, Barbara T. "Robotic path planning with obstacle avoidance /." Online version of thesis, 1993. http://hdl.handle.net/1850/11712.
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Crous, C. B. "Autonomous robot path planning." Thesis, Stellenbosch : University of Stellenbosch, 2009. http://hdl.handle.net/10019.1/2519.
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Thesis (MSc (Mathematical Sciences. Computer SCience))--University of Stellenbosch, 2009.In this thesis we consider the dynamic path planning problem for robotics. The dynamic path planning problem, in short, is the task of determining an optimal path, in terms of minimising a given cost function, from one location to another within a known environment of moving obstacles. Our goal is to investigate a number of well-known path planning algorithms, to determine for which circumstances a particular algorithm is best suited, and to propose changes to existing algorithms to make them perform better in dynamic environments. At this stage no thorough comparison of theoretical and actual running times of path planning algorithms exist. Our main goal is to address this shortcoming by comparing some of the wellknown path planning algorithms and our own improvements to these path planning algorithms in a simulation environment. We show that the visibility graph representation of the environment combined with the A* algorithm provides very good results for both path length and computational cost, for a relatively small number of obstacles. As for a grid representation of the environment, we show that the A* algorithm produces good paths in terms of length and the amount of rotation and it requires less computation than dynamic algorithms such as D* and D* Lite.
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Dragan, Anca D. "Legible Robot Motion Planning." Research Showcase @ CMU, 2015. http://repository.cmu.edu/dissertations/629.
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The goal of this thesis is to enable robots to produce motion that is suitable for human-robot collaboration and co-existence. Most motion in robotics is purely functional: industrial robots move to package parts, vacuuming robots move to suck dust, and personal robots move to clean up a dirty table. This type of motion is ideal when the robot is performing a task in isolation. Collaboration, however, does not happen in isolation. In collaboration, the robot’s motion has an observer, watching and interpreting the motion. In this work, we move beyond functional motion, and introduce the notion of an observer into motion planning, so that robots can generate motion that is mindful of how it will be interpreted by a human collaborator. We formalize predictability and legibility as properties of motion that naturally arise from the inferences that the observer makes, drawing on action interpretation theory in psychology. Predictable motion stems from a goal-to-action inference and matches the observer’s expectation, given the robot’s goal. Legible motion stems from an action-to-goal inference: the robot is clearly conveying its goal with its ongoing motion. We propose models for these inferences based on the principle of rational action, Bayesian inference, and the principle of maximum entropy. We then use a combination of constrained trajectory optimization and machine learning techniques to enable robots to plan motion that is predictable or legible. Finally, we verify that the generated motions are more predictable and legible, and evaluate the impact of such motion on a physical human-robot collaboration task. Our results suggest that predictability and legibility do not only increase task performance, but also make the collaboration process more fluent, increasing subjective metrics such as trust or comfort. We also show generalizations of the legibility formalism to deception, gestures, and assistive teleoperation.
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Wooden, David T. "Graph-based Path Planning for Mobile Robots." Diss., Available online, Georgia Institute of Technology, 2006, 2006. http://etd.gatech.edu/theses/available/etd-11092006-180958/.
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Thesis (Ph. D.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2007.Magnus Egerstedt, Committee Chair ; Patricio Vela, Committee Member ; Ayanna Howard, Committee Member ; Tucker Balch, Committee Member ; Wayne Book, Committee Member.
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Akan, Batu. "Planning and Sequencing Through Multimodal Interaction for Robot Programming." Doctoral thesis, Mälardalens högskola, Inbyggda system, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-26474.
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Over the past few decades the use of industrial robots has increased the efficiency as well as the competitiveness of several sectors. Despite this fact, in many cases robot automation investments are considered to be technically challenging. In addition, for most small and medium-sized enterprises (SMEs) this process is associated with high costs. Due to their continuously changing product lines, reprogramming costs are likely to exceed installation costs by a large margin. Furthermore, traditional programming methods of industrial robots are too complex for most technicians or manufacturing engineers, and thus assistance from a robot programming expert is often needed. The hypothesis is that in order to make the use of industrial robots more common within the SME sector, the robots should be reprogrammable by technicians or manufacturing engineers rather than robot programming experts. In this thesis, a novel system for task-level programming is proposed. The user interacts with an industrial robot by giving instructions in a structured natural language and by selecting objects through an augmented reality interface. The proposed system consists of two parts: (i) a multimodal framework that provides a natural language interface for the user to interact in which the framework performs modality fusion and semantic analysis, (ii) a symbolic planner, POPStar, to create a time-efficient plan based on the user's instructions. The ultimate goal of this work in this thesis is to bring robot programming to a stage where it is as easy as working together with a colleague.This thesis mainly addresses two issues. The first issue is a general framework for designing and developing multimodal interfaces. The general framework proposed in this thesis is designed to perform natural language understanding, multimodal integration and semantic analysis with an incremental pipeline. The framework also includes a novel multimodal grammar language, which is used for multimodal presentation and semantic meaning generation. Such a framework helps us to make interaction with a robot easier and more natural. The proposed language architecture makes it possible to manipulate, pick or place objects in a scene through high-level commands. Interaction with simple voice commands and gestures enables the manufacturing engineer to focus on the task itself, rather than the programming issues of the robot. The second issue addressed is due to inherent characteristics of communication with the use of natural language; instructions given by a user are often vague and may require other actions to be taken before the conditions for applying the user's instructions are met. In order to solve this problem a symbolic planner, POPStar, based on a partial order planner (POP) is proposed. The system takes landmarks extracted from user instructions as input, and creates a sequence of actions to operate the robotic cell with minimal makespan. The proposed planner takes advantage of the partial order capabilities of POP to execute actions in parallel and employs a best-first search algorithm to seek the series of actions that lead to a minimal makespan. The proposed planner can also handle robots with multiple grippers, parallel machines as well as scheduling for multiple product types.
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Cakmak, Maya. "Robot Planning Based On Learned Affordances." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608551/index.pdf.
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This thesis studies how an autonomous robot can learn affordances from its interactions with the environment and use these affordances in planning. It is based on a new formalization of the concept which proposes that affordances are relations that pertain to the interactions of an agent with its environment. The robot interacts with environments containing different objects by executing its atomic actions and learns the different effects it can create, as well as the invariants of the environments that afford creating that effect with a certain action. This provides the robot with the ability to predict the consequences of its future interactions and to deliberatively plan action sequences to achieve a goal. The study shows that the concept of affordances provides a common framework for studying reactive control, deliberation and adaptation in autonomous robots. It also provides solutions to the major problems in robot planning, by grounding the planning operators in the low-level interactions of the robot.
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Marshall, Gillian Fiona. "Resistive grids for robot path-planning." Thesis, University of Oxford, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.317916.
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Kent, Simon. "Evolutionary Approaches to Robot Path Planning." Thesis, Brunel University, 1999. http://bura.brunel.ac.uk/handle/2438/1276.
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The ultimate goal in robotics is to create machines which are more independent and rely less on humans to guide them in their operation. There are many sub-systems which may be present in such a robot, one of which is path planning — the ability to determine a sequence of positions or configurations between an initial and goal position within a particular obstacle cluttered workspace. Many classical path planning techniques have been developed, but these tend to have drawbacks such as their computational requirements; the suitability of the plans they produce for a particular application; or how well they are able to generalise to unseen problems. In recent years, evolutionary based problem solving techniques have seen a rise in popularity, possibly coinciding with the improvement in the computational power afforded researches by successful developments in hardware. These techniques adopt some of the features of natural evolution and mimic them in a computer. The increase in the number of publications in the areas of Genetic Algorithms (GA) and Genetic Programming (GP) demonstrate the success achieved when applying these techniques to ever more problem areas. This dissertation presents research conducted to determine whether there is a place for Evolutionary Approaches, and specifically GA and GP, in the development of future path planning techniques.
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Sanders, David Adrian. "Automatic robot path planning with constraints." Thesis, University of Portsmouth, 1990. https://researchportal.port.ac.uk/portal/en/theses/automatic-robot-path-planning-with-constraints(8b5bedfa-68c2-40ac-afad-c318a5037305).html.
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In a complex and flexible manufacturing environment tasks maybe dynamically reconfigured. In this situation a robot needs to plan paths automatically to avoid obstacles and rendezvous with changing target points. A novel path planning system is presented which takes into account both kinematic and dynamic constraints. The main part of the system comprises a robot "Path Planner" and "Path Adapter", both using a dynamic "World Model" updated by a vision system. The Path Planner contains a geometric model of the static environment and the robot. Given a task, the Path Planner calculates an efficient collision free path. This is passed to the control computer where a trajectory is generated. Pre-determination of optimum paths using established techniques frequently involve unacceptably high time penalties. To overcome this problem the automatic path refinement techniques employed avoid the necessity for optimality before beginning a movement. Repeated improvements to the sub optimal paths initially generated by the Path Planner are made until the robot is ready to begin the new path. Algorithms are presented which give a rapid solution for simplified obstacle models. The algorithms are robust and are especially suitable for repetitive robot tasks. With the Path Planner, the robot structure is modelled as connected cylinders and spheres and the range of robot motion is quantised. The robot path, calculated initially only takes account of geometric, kinematic and obstacle constraints. Although this path is sub optimal, the calculation time is short. The path avoids obstacle and seeks the "shortest" path in terms of total actuator movement. Several of the new path planning methods presented employ a local method, taking a "best guess" at a path through a 2-D space for two joints and then calculating a path for the third joint such that obstacles are avoided. A different approach is global and depends on searching a 3-D graph of quantised joint space. The Path Planner works in real time. If there is enough time available a "Path Adapter" modifies the planned path in an effort to improve the path subject to selected criteria. The Path Adapter considers dynamic constraints. The first robot path improvement method depends on detecting the joint motor currents in order to minimise changes in joint direction, the other is based on a set of adaptive rules based on simplified dynamic software models of the robot stored within the planning computer. The adapted path is passed to the control computer. The static model of the robot work-cell is held in computer memory as several solid polyhedral. With the aid of a vision system, this model is updated as new obstacles enter or leave the work-place. Overlapping spheres and 2-D slices in joint space are used to model obstacles. In this form the vision system can be updated quickly and the obstacle data can de accessed efficiently by the path planning and path improvement algorithms.
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Buttar, Harmandeep Kaur. "Multi Robot Motion Planning with Communication." University of Cincinnati / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1337264354.
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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 roboticienThis 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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Pluzhnikov, Sergey. "Motion Planning and Control of Robot Manipulators." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for teknisk kybernetikk, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-18437.
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When a robot performs a task in an unstructured dynamic environment, it has to account for many factors. It should not only keep the track of where it is and how it should move, but also ensure that the kinematic, dynamic and task specific limitations are observed. It is also important that the robot can effectively avoid collisions with static and moving obstacles. In the current thesis we present design and implementation of an algorithm capable to face all these challenges. The system combines principles of dynamic roadmaps and elastic roadmaps frameworks, both of which are the state-of-art approaches to motion planning problem. The suggested solution is presented in the context of a broad overview of the literature in motion planning domain focusing on methodology of sample-based and feedback planning in dynamic environments. The implemented algorithm is applied to a 7-degree-of-freedom manipulator and is demonstrated and analyzed through a variety of simulated test scenarios. The result is an extensible and future-oriented planning system that can plan and execute movement between a starting and target position while preserving task constraints and reacting to environment changes in real time.
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Dornhege, Christian [Verfasser], and Bernhard [Akademischer Betreuer] Nebel. "Task planning for high-level robot control." Freiburg : Universität, 2015. http://d-nb.info/1114996319/34.
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Baumann, Andrea. "Robot motion planning in time varying environments." [S.l.] : [s.n.], 2001. http://deposit.ddb.de/cgi-bin/dokserv?idn=963283677.
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Chang, Mark Meng-Hsiang. "Distributed multi-robot planning using shared perception /." [St. Lucia, Qld.], 2004. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe19027.pdf.
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Strandberg, Morten. "Robot path planning : an object-oriented approach." Doctoral thesis, KTH, Signals, Sensors and Systems, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-18.
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Path planning has important applications in many areas, for example industrial robotics, autonomous systems, virtual prototyping, and computer-aided drug design. This thesis presents a new framework for developing and evaluating path planning algorithms. The framework is named CoPP (Components for Path Planning). It consists of loosely coupled and reusable components that are useful for building path planning applications. The framework is especially designed to make it easy to do fair comparisons between different path planning algorithms.
CoPP is also designed to allow almost any user-defined moving system. The default type of moving system is a robot class, which is capable of describing tree-like kinematic chains. Additional features of this robot class are: joint couplings, numerical or closed-form inverse kinematics, and hierarchical robot representations. The last feature is useful when planning for complex systems like a mobile platform equipped with an arm and a hand.
During the last six years, Rapidly-exploring Random Trees (RRTs) have become a popular framework for developing randomized path planning algorithms. This thesis presents a method for augmenting bidirectional RRT-planners with local trees. For problems where the solution trajectory has to pass through several narrow passages, local trees help to reduce the required planning time.
To reduce the work needed for programming of industrial robots, it is desirable to allow task specifications at a very high level, leaving it up to the robot system to figure out what to do. Here we present a fast and flexible pick-and-place planner. Given an object that has to be moved to another position, the planner chooses a suitable grasp of the object and finds motions that bring the object to the desired position. The planner can also handle constraints on, e.g., the orientation of the manipulated object.
For planning of pick-and-place tasks it is necessary to choose a grasp suitable to the task. Unless the grasp is given, some sort of grasp planning has to be performed. This thesis presents a fast grasp planner for a three- fingered robot hand. The grasp planner could be used in an industrial setting, where a robot is to pick up irregularly shaped objects from a conveyor belt. In conjunction with grasp planning, a new method for evaluating grasp stability is presented.
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Bonert, Martin. "Motion planning for multi-robot assembly systems." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape8/PQDD_0004/MQ45428.pdf.
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Peng, Jian. "Rule-based spatial reasoning for robot planning." Thesis, University of Oxford, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.315818.
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Gonzalez, Julio Solano. "Parallel computation of robot motion planning algorithms." Thesis, Bangor University, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.305960.
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Pilati, Matteo. "Motion planning techniques for parallel robot manipulators." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2012. http://amslaurea.unibo.it/4816/.
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Brown, Matthew Lasché. "Intelligent robot grinding : planning, optimization, and control." Thesis, Massachusetts Institute of Technology, 1988. http://hdl.handle.net/1721.1/14552.
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Balding, Nigel William. "Real-time path planning for robot arms." Thesis, Durham University, 1987. http://etheses.dur.ac.uk/1681/.
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Zhao, Ran. "Trajectory planning and control for robot manipulations." Thesis, Toulouse 3, 2015. http://www.theses.fr/2015TOU30240/document.
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Comme les robots effectuent de plus en plus de tâches en interaction avec l'homme ou dans un environnement humain, ils doivent assurer la sécurité et le confort des hommes. Dans ce contexte, le robot doit adapter son comportement et agir en fonction des évolutions de l'environnement et des activités humaines. Les robots développés sur la base de l'apprentissage ou d'un planificateur de mouvement ne sont pas en mesure de réagir assez rapidement, c'est pourquoi nous proposons d'introduire un contrôleur de trajectoire intermédiaire dans l'architecture logicielle entre le contrôleur bas niveau et le planificateur de plus haut niveau. Le contrôleur de trajectoire que nous proposons est basé sur le concept de générateur de trajectoire en ligne (OTG), il permet de calculer des trajectoires en temps réel et facilite la communication entre les différents éléments, en particulier le planificateur de chemin, le générateur de trajectoire, le détecteur de collision et le contrôleur. Pour éviter de replanifier toute une trajectoire en réaction à un changement induit par un humain, notre contrôleur autorise la déformation locale de la trajectoire et la modification de la loi d'évolution pour accélérer ou décélérer le mouvement. Le contrôleur de trajectoire peut également commuter de la trajectoire initiale vers une nouvelle trajectoire. Les fonctions polynomiales cubiques que nous utilisons pour décrire les trajectoires fournissent des mouvements souples et de la flexibilité sans nécessiter de calculs complexes. De plus, les algorithmes de lissage que nous proposons permettent de produire des mouvements esthétiques ressemblants à ceux des humains. Ce travail, mené dans le cadre du projet ANR ICARO, a été intégré et validé avec les robots KUKA LWR de la plate-forme robotique du LAAS-CNRSIn order to perform a large variety of tasks in interaction with human or in human environments, a robot needs to guarantee safety and comfort for humans. In this context, the robot shall adapt its behavior and react to the environment changes and human activities. The robots based on learning or motion planning are not able to adapt fast enough, so we propose to use a trajectory controller as an intermediate control layer in the software structure. This intermediate layer exchanges information with the low level controller and the high level planner. The proposed trajectory controller, based on the concept of Online Trajectory Generation (OTG), allows real time computation of trajectories and easy communication with the different components, including path planner, trajectory generator, collision checker and controller. To avoid the replan of an entire trajectory when reacting to a human behaviour change, the controller must allow deforming locally a trajectory or accelerate/decelerate by modifying the time function. The trajectory controller must also accept to switch from an initial trajectory to a new trajectory to follow. Cubic polynomial functions are used to describe trajectories, they provide smoothness, flexibility and computational simplicity. Moreover, to satisfy the objective of aesthetics, smoothing algorithm are proposed to produce human-like motions. This work, conducted as part of the ANR project ICARO, has been integrated and validated on the KUKA LWR robot platform of LAAS-CNRS
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Kelsey, Lundqvist Axel, and Fabian Tidner. "High Level Motion Planning for a Robot." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254213.
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Robots and automated systems are becoming an ever present part of modern life. The simplicity with which a technology can be used by people without a technological background is paramount to its adoption by the general public. What is presented here is a simple framework for users to give high level motion control commands without sacrificing technological complexity. This is accomplished by using a control synthesis for high level phrases. A user enters high level commands expressed in Linear Temporal Logic which the system interprets and then a robot goes on to perform. As such the entirety of the logical inputs needed for completed motion planning is encompassed within one simple phrase. The problem has been approached two different ways, one that prioritizes computational speed and another with a higher degree of optimization. Both of these framework works well for a multitude of different rooms and commands and form a basis for further works in the subject. What sets this research apart is the inclusion of Büchi minimisation based on the research by [1] in a high level motion planning system. This notably reduces computation time for more complicated LTL phrases. [1]
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MARTURI, ANJANILAKSHMIKRISNANARESH. "Vision Based Grasp Planning for Robot Assembly." Thesis, Örebro universitet, Akademin för naturvetenskap och teknik, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-12402.
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Liu, Zehao. "Obstacle Avoidance Path Planning for Worm-like Robot." Case Western Reserve University School of Graduate Studies / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=case1619457610715525.
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Pandey, Saurabh. "Motion planning of free-floating prismatic-jointed robots." Ohio : Ohio University, 1996. http://www.ohiolink.edu/etd/view.cgi?ohiou1178049680.
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Kothandaraman, Kaamesh. "Motion Planning and Control of Differential Drive Robot." Wright State University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=wright1483909837910426.
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Haight, Timothy A. "Layered path planning for an autonomous mobile robot." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1994. http://handle.dtic.mil/100.2/ADA286138.
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Thesis (M.S. in Computer Science and M.S. in Mathematics) Naval Postgraduate School, September 1994.Thesis advisor(s): Yutaka Kanayama, Craig W. Rasmussen. "September 1994." Bibliography: p. 43-44. Also available online.
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Papadatos, Athanassios. "Research on motion planning of autonomous mobile robot." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1996. http://handle.dtic.mil/100.2/ADA311383.
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Johansson, Ronnie. "Intelligent Motion Planning for a Multi-Robot System." Thesis, KTH, Numerical Analysis and Computer Science, NADA, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-13253.
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Multi-robot systems of autonomous mobile robots offer many benefits but also many challenges. This work addresses collision avoidance of robots solving continuous problems in known environments. The approach to handling collision avoidance is here to enhance a motion planning method for single-robot systems to account for auxiliary robots. A few assumptions are made to put the focus of the work on path planning, rather than on localization.
A method, based on exact cell decomposition and extended with a few rules, was developed and its consistency was proven. The method is divided into two steps: path planning, which is off-line, and path monitoring, which is on-line. This work also introduces the notion ofpath obstacle, an essential tool for this kind of path planning with many robots.
Furthermore, an implementation was performed on a system of omni-directional robots and tested in simulations and experiments. The implementation practices centralized control, by letting an additional computer handle the motion planning, to relieve the robots of strenuous computations.
A few drawbacks with the method are stressed, and the characteristics of problems that the method is suitable for are presented.
QC 20100705
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Doyle, Alexander Benjamin. "Algorithms and computational techniques for robot path planning." Thesis, Bangor University, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.295278.
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Jahanbin, Mohammad Reza. "A model-based system for robot motion planning." Thesis, University of Cambridge, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.291721.
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Bradner, Kevin M. "Path Planning for Variable Scrutiny Multi-Robot Coverage." Case Western Reserve University School of Graduate Studies / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=case1578915876868832.
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ABU-DAKKA, FARES JAWAD MOHD. "Trajectory planning for industrial robot using genetic algorithms." Doctoral thesis, Universitat Politècnica de València, 2011. http://hdl.handle.net/10251/10294.
Full textAbstract:
En las últimas décadas, debido la importancia de sus aplicaciones, se han propuesto muchas investigaciones sobre la planificación de caminos y trayectorias para los manipuladores, algunos de los ámbitos en los que pueden encontrarse ejemplos de aplicación son; la robótica industrial, sistemas autónomos, creación de prototipos virtuales y diseño de fármacos asistido por ordenador. Por otro lado, los algoritmos evolutivos se han aplicado en muchos campos, lo que motiva el interés del autor por investigar sobre su aplicación a la planificación de caminos y trayectorias en robots industriales.
En este trabajo se ha llevado a cabo una búsqueda exhaustiva de la literatura existente relacionada con la tesis, que ha servido para crear una completa base de datos utilizada para realizar un examen detallado de la evolución histórica desde sus orígenes al estado actual de la técnica y las últimas tendencias.
Esta tesis presenta una nueva metodología que utiliza algoritmos genéticos para desarrollar y evaluar técnicas para la planificación de caminos y trayectorias. El conocimiento de problemas específicos y el conocimiento heurístico se incorporan a la codificación, la evaluación y los operadores genéticos del algoritmo.
Esta metodología introduce nuevos enfoques con el objetivo de resolver el problema de la planificación de caminos y la planificación de trayectorias para sistemas robóticos industriales que operan en entornos 3D con obstáculos estáticos, y que ha llevado a la creación de dos algoritmos (de alguna manera similares, con algunas variaciones), que son capaces de resolver los problemas de planificación mencionados.
El modelado de los obstáculos se ha realizado mediante el uso de combinaciones de objetos geométricos simples (esferas, cilindros, y los planos), de modo que se obtiene un algoritmo eficiente para la prevención de colisiones.
El algoritmo de planificación de caminos se basa en técnicas de
optimización globales, usando algoritmos genéticos para minimizar una función
objetivo considerando restricciones para evitar las colisiones con los obstáculos. El
camino está compuesto de configuraciones adyacentes obtenidas mediante una
técnica de optimización construida con algoritmos genéticos, buscando minimizar
una función multiobjetivo donde intervienen la distancia entre los puntos
significativos de las dos configuraciones adyacentes, así como la distancia desde
los puntos de la configuración actual a la final. El planteamiento del problema
mediante algoritmos genéticos requiere de una modelización acorde al
procedimiento, definiendo los individuos y operadores capaces de proporcionar
soluciones eficientes para el problema.Abu-Dakka, FJM. (2011). Trajectory planning for industrial robot using genetic algorithms [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/10294
Palancia
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Chanin, Steven Bruce. "Guesser--a heuristic approach to robot motion planning." Thesis, Massachusetts Institute of Technology, 1991. https://hdl.handle.net/1721.1/128803.
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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1991.Includes bibliographical references (leaves 88-89).
by Steven Bruce Chanin.
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1991.
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Mendes, Filho José. "Online Distributed Motion Planning for Mobile Multi-robot Systems." Thesis, Institut polytechnique de Paris, 2019. http://www.theses.fr/2019IPPAE007.
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Les objectifs principaux de la thèse sont les suivants : - Concevoir un système multi-robots mobiles autonomes capable d'exécuter des tâches complexes dans un environnement dynamique, partialement connu ; - Assurer la sécurité des biens et une interaction homme-robot approprié dans un environnement de travail partagé. Pour ce faire on propose une solution en 3 couches intégrées listées ci-dessous : - Une commande - Une planification de mouvements - Une planification de tâches Le développement de chaque partie de la solution est validé en simulation suivi par une validation par des essaies réels avec des plateformes mobiles (e.g. TurtleBots). Les résultats seront analysés à l’égard des besoins dérivées des objectives présentés au débutTwo main objectives for this thesis can be identified: - Develop a multi-robot system composed by autonomous mobile robots capable of performing complex tasks in a dynamic, partially known environment; - Ensure the safety of goods and a proper interaction human-robot in their shared work environment. To that purpose a 3 layer solution is proposed containing : - Control law - Motion planner - Task planner Each layer is validated firstly in simulation and secondly in a real experiment using mobile platforms such as TurtleBots. The found results will be analysed with respect to requirements derived from the objectives stated at the beginning
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Ward, James Robert Mechanical & Manufacturing Engineering Faculty of Engineering UNSW. "Motion planning of bipedal wall climbing robots." Publisher:University of New South Wales. Mechanical & Manufacturing Engineering, 2009. http://handle.unsw.edu.au/1959.4/43685.
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The development of wall climbing robots is relatively recent, beginning with some large scale robots in the early 1990s. Wall climbing robots can be used to gain access to or inspect space that is not easily accessible or dangerous for human operators. The range of applicable fields encompasses industrial processes and inspection, exploration, rescue and monitoring. The smaller robots can be used for surveillance purposes due to their stealthy nature. Larger crawling robots may be used to carry out specific tasks such as sand blasting of ship hulls and blasting and spray painting of large containers such as cylindrical storage tanks used by the chemical, petroleum and nuclear industries. Their flexibility and mobility mean that they can accomplish tasks that would be impossible for more conventional robots. The flexibility of mobility that such robots gain from their ability to move on all surfaces rather than only horizontal ones creates some unique challenges. Broadly, they can be split into three categories: robot design, robot control and motion planning, and environmental mapping and localisation. This thesis examines the first two of these problems. A prototype bipedal robot has been built and a second designed in order to capitalise on the experience gained with the first. An in-depth examination of the motion planning problem has been made and new techniques to tackle this problem have been developed. Such techniques are not limited to applications with wall climbing robots as there is commonality with more traditional fixed manipulators. Finally, the planning techniques were combined with the robot design in a test scenario that validated both the design and the motion planning techniques developed throughout the dissertation.
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Quinn, Andrew W. "Motion planning for manipulators using distributed search." Thesis, Heriot-Watt University, 1993. http://hdl.handle.net/10399/1439.
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rahman, md mahbubur. "Efficient Mission Planning for Robot Networks in Communication Constrained Environments." FIU Digital Commons, 2017. http://digitalcommons.fiu.edu/etd/3484.
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Many robotic systems are remotely operated nowadays that require uninterrupted connection and safe mission planning. Such systems are commonly found in military drones, search and rescue operations, mining robotics, agriculture, and environmental monitoring. Different robotic systems may employ disparate communication modalities such as radio network, visible light communication, satellite, infrared, Wi-Fi. However, in an autonomous mission where the robots are expected to be interconnected, communication constrained environment frequently arises due to the out of range problem or unavailability of the signal. Furthermore, several automated projects (building construction, assembly line) do not guarantee uninterrupted communication, and a safe project plan is required that optimizes collision risks, cost, and duration. In this thesis, we propose four pronged approaches to alleviate some of these issues: 1) Communication aware world mapping; 2) Communication preserving using the Line-of-Sight (LoS); 3) Communication aware safe planning; and 4) Multi-Objective motion planning for navigation.
First, we focus on developing a communication aware world map that integrates traditional world models with the planning of multi-robot placement. Our proposed communication map selects the optimal placement of a chain of intermediate relay vehicles in order to maximize communication quality to a remote unit. We also vi propose an algorithm to build a min-Arborescence tree when there are multiple remote units to be served. Second, in communication denied environments, we use Line-of-Sight (LoS) to establish communication between mobile robots, control their movements and relay information to other autonomous units. We formulate and study the complexity of a multi-robot relay network positioning problem and propose approximation algorithms that restore visibility based connectivity through the relocation of one or more robots. Third, we develop a framework to quantify the safety score of a fully automated robotic mission where the coexistence of human and robot may pose a collision risk. A number of alternate mission plans are analyzed using motion planning algorithms to select the safest one. Finally, an efficient multi-objective optimization based path planning for the robots is developed to deal with several Pareto optimal cost attributes.
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Canal, Camprodon Gerard. "Adapting robot behavior to user preferences in assistive scenarios." Doctoral thesis, TDX (Tesis Doctorals en Xarxa), 2020. http://hdl.handle.net/10803/669799.
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Robotic assistants have inspired numerous books and science fiction movies.
In the real world, these kinds of devices are a growing need in amongst the elderly, who while life continue requiring more assistance. While life expectancy is increasing, life quality is not necessarily doing so. Thus, we may find ourselves and our loved ones being dependent and needing another person to perform the most basic tasks, which has a strong psychological impact. Accordingly, assistive robots may be the definitive tool to give more quality of life by empowering dependent people and extending their independent living.
Assisting users to perform daily activities requires adapting to them and their needs, as they might not be able to adapt to the robot.
This thesis tackles adaptation and personalization issues through user preferences. We 'focus on physical tasks that involve close contact, as these present interesting challenges, and are of great importance for he user. Therefore, three tasks are mainly used throughout the thesis: assistive feeding, shoe fitting, and jacket dressing. We first describe a framework for robot behavior adaptation that illustrates how robots should be personalized for and by end- users or their assistants. Using this framework, non-technical users determine how !he robot should behave. Then, we define the concept of preference for assistive robotics scenarios and establish a taxonomy, which includes hierarchies and groups of preferences, grounding definitions and concepts. We then show how the preferences in the taxonomy are used with Al planning systems to adapt the robot behavior to the preferences of the user obtained from simple questions. Our algorithms allow for long-term adaptations as well as to cope with misinformed user models. We further integrate the methods with low-level motion primitives that provide a more robust adaptation and behavior while lowering the number of needed actions and demonstrations. Moreover, we perform a deeper analysis in Planning and preferences with the introduction of new algorithms to provide preference suggestions in planning domains. The thesis then concludes with a user study that evaluates the use of the preferences in the three real assistive robotics scenarios. The experiments show a clear understanding of the preferences of users, who were able to assess the impact of their preferences on the behavior of the robot.
In summary, we provide tools and algorithms to design the robotic assistants of the future. Assistants that should be able to adapt to the assisted user needs and preferences, just as human assistants do nowadays.Els assistents robòtics han inspirat nombrosos llibres i pel·lícules de ciència-ficció al llarg de la història. Però tornant al món real, aquest tipus de dispositius s'estan tornant una necessitat per a una societat que envelleix a un ritme ràpid i que, per tant, requerirà més i més assistència. Mentre l'esperança de vida augmenta, la qualitat de vida no necessàriament ho fa. Per tant, ens podem trobar a nosaltres mateixos i als nostres estimats en una situació de dependència, necessitant una altra persona per poder fer les tasques més bàsiques, cosa que té un gran impacte psicològic. En conseqüència, els robots assistencials poden ser l'eina definitiva per proporcionar una millor qualitat de vida empoderant els usuaris i allargant la seva capacitat de viure independentment. L'assistència a persones per realitzar tasques diàries requereix adaptar-se a elles i les seves necessitats, donat que aquests usuaris no poden adaptar-se al robot. En aquesta tesi, abordem el problema de l'adaptació i la personalització d'un robot mitjançant preferències de l'usuari. Ens centrem en tasques físiques, que involucren contacte amb la persona, per les seves dificultats i importància per a l'usuari. Per aquest motiu, la tesi utilitzarà principalment tres tasques com a exemple: donar menjar, posar una sabata i vestir una jaqueta. Comencem definint un marc (framework) per a la personalització del comportament del robot que defineix com s'han de personalitzar els robots per usuaris i pels seus assistents. Amb aquest marc, usuaris sense coneixements tècnics són capaços de definir com s'ha de comportar el robot. Posteriorment definim el concepte de preferència per a robots assistencials i establim una taxonomia que inclou jerarquies i grups de preferències, els quals fonamenten les definicions i conceptes. Després mostrem com les preferències de la taxonomia s'utilitzen amb sistemes planificadors amb IA per adaptar el comportament del robot a les preferències de l'usuari, que s'obtenen mitjançant preguntes simples. Els nostres algorismes permeten l'adaptació a llarg termini, així com fer front a models d'usuari mal inferits. Aquests mètodes són integrats amb primitives a baix nivell que proporcionen una adaptació i comportament més robusts a la mateixa vegada que disminueixen el nombre d'accions i demostracions necessàries. També fem una anàlisi més profunda de l'ús de les preferències amb planificadors amb la introducció de nous algorismes per fer suggeriments de preferències en dominis de planificació. La tesi conclou amb un estudi amb usuaris que avalua l'ús de les preferències en les tres tasques assistencials. Els experiments demostren un clar enteniment de les preferències per part dels usuaris, que van ser capaços de discernir quan les seves preferències eren utilitzades. En resum, proporcionem eines i algorismes per dissenyar els assistents robòtics del futur. Uns assistents que haurien de ser capaços d'adaptar-se a les preferències i necessitats de l'usuari que assisteixen, tal com els assistents humans fan avui en dia.
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Behere, Sagar. "A Generic Framework for Robot Motion Planning and Control." Thesis, KTH, Centrum för Autonoma System, CAS, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-104806.
Full textAbstract:
This thesis deals with the general problem of robot motion planning and control. It proposes the hypothesis that it should bepossible to create a generic software framework capable of dealing with all robot motion planning and control problems, independent of the robot being used, the task being solved, the workspace obstacles or the algorithms employed. The thesis work then consisted of identifying the requirements and creating a design and implementation of such a framework. This report motivates and documents the entire process. The framework developed was tested on two different robot arms under varying conditions. The testing method and results are also presented.The thesis concludes that the proposed hypothesis is indeed valid.
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Yun, Seok Jun. "The local motion planning for an autonomous mobile robot." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1995. http://handle.dtic.mil/100.2/ADA304359.
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"Grasp planning in discrete domain." 2002. http://library.cuhk.edu.hk/record=b5891098.
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by Lam Miu-Ling.Thesis (M.Phil.)--Chinese University of Hong Kong, 2002.
Includes bibliographical references (leaves 64-67).
Abstracts in English and Chinese.
Chapter Chapter 1. --- Introduction --- p.1
Chapter Chapter 2. --- Mathematical Preliminaries and Problem Definition --- p.6
Chapter 2.1 --- Grasp Synthesis in Discrete Domain
Chapter 2.2 --- Assumptions
Chapter 2.3 --- Frictionless Form-Closure Grasp
Chapter 2.4 --- Frictional Form-Closure Grasp
Chapter 2.5 --- Problem Definition
Chapter Chapter 3. --- A Qualitative Test Algorithm and a Local Search Algorithm --- p.18
Chapter 3.1 --- A Qualitative Test Algorithm
Chapter 3.2 --- A Local Search Algorithm
Chapter 3.3 --- Grasp Planning under Kinematic Constraints
Chapter Chapter 4. --- A Divide-and-Conquer Technique --- p.29
Chapter 4.1. --- Determining a Separating Hyperplane
Chapter 4.2. --- Divide-and-Conquer in Frictionless Case
Chapter 4.3. --- Divide-and-Conquer in Frictional Case
Chapter Chapter 5. --- Implementation and Examples --- p.40
Chapter 6.1. --- Examples of Frictionless Grasps
Chapter 6.2. --- Examples of Frictional Grasps
Chapter 6.3. --- Examples of Grasps under Kinematic Constraints
Chapter Chapter 6. --- Conclusions --- p.62
Bibliography --- p.64
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Chen, Bo-Yu, and 陳柏宇. "Failure Robot Path Complementation for Robot Swarm Mission Planning." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/856bdw.
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碩士國立虎尾科技大學
自動化工程系碩士班
105
Unmanned vehicle is applied widely in environmental explorations nowadays, especially for the tasks where human beings are not able to reach. Due to limited capacities like power supply, it is almost impossible for any single one unmanned vehicle to complete a large assignment with multiple designated location to visit. As well as failure robot task won’t complemented when each car failing. Therefore, multiple unmanned vehicles (Multi-Agent System, MAS) are required as well as the well-planned routes to minimize unnecessary consumption and waste on time, distance and energy/fuels needed. In addition, robot cars are able to avoid no-travel zone and the task of failure robot was complemented by the other. Same as other large mathematic model, heuristic algorithm was used to obtain an approximate solution within a reasonable timeline for this research. First, establish distance array. If any two points through the no-travel zone, use A^* algorithm to find the alternative path to avoid no-travel zone. Then, a two-phase architecture was applied. In the 1st phase, Tabu search and 2-Opt exchange method were used to figure out the optimal path for visiting all target nodes, and then the initial solution by splitting it into multiple clusters. In the 2nd phase, the algorithm was used with 2-Opt path exchange were used to improve the in-route and cross-route solutions. Diversification strategy was adopted to approach the global optimal solution rather than a regional one. Once the objectives mentioned above were accomplished, we dispatched several robot cars to operate simultaneously on the routes we planned ahead. If one of the autonomous cars failing, new path will be programmed and reassigned to autonomous car of remaining by the ground station. until all the target points are visited. In the end, computer simulations and real vehicle had been accomplished in this research.
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YANG, HU-CHENG, and 楊戶政. "Robot Path Planning Navigation Design." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/40045055091804835187.
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碩士建國科技大學
電機工程系暨研究所
102
This paper is designed to Navigation the robot path planning in the restaurant or convenience store on the Navigator application integration, mobile robot kinematics systems analysis, and single board computers to microchips BASIC Commander as the core, and establish a sense infrared detectors, voice player, ultrasonic sensors based mobile robot Navigation system, and the use of multi-sensor integration of information technology, as input Fuzzy adaptive principle, according to the fuzzy control rules, get the motor control query table that has a strong anti-collision path tracking and the ability to robots. Through simulation and actual verification that the system is stable robot path planning Navigation with simple, fast response, robustness and good features, while having a guide wire in the environment can effectively present mobile robot navigation.
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Sue, Geng-Hong, and 蘇建宏. "Robot path planning using fuzzy theory." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/44377019345965098693.
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碩士國立成功大學
電機工程研究所
82
Path planning is an important task in a robot vision system. In thesis, a new approach to the problem of path finding of a robot using fuzzy theory is proposed. A learning algorithm based on back-propagation with gradient descent is also proposed to train the fuzzy network. The proposed algorithm combines the fuzzy theory, the distance transform, and the potential field method to plan a smooth and safe path to guide a robot to the destination. From an input image of the enviroment, distance transform is used to obtain the distance between a robot and the obstacles. The potential field method is used to calculate the attractive and repulsive forces between a robot and the obstacles. Combining fuzzy logic, distance transforms, and the potential field method, a robot can be guided to the destination. A problem that a robot becomes trapped at a local minimum in the navigating mode may exist. In the case, the robot is swithed to the tracking mode. Finally, a learning algorithm is proposed to tune the membership function to control the robot to the desired path.
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Wu, Zih-Yan, and 吳治彥. "Restaurant Service Robot of Path Planning." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/73461238619136885963.
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碩士吳鳳科技大學
光機電暨材料研究所
99
In this thesis we use the platform with two wheels of differential drive as the carrier of restaurant service robot, and utilize different methods to measure the travel path error of the robot so as to be the basis for control. First, without using SICK (SICK AG company, Germany) laser positioning system, we drove the robot to move in several preset paths using water dropping device to record the actual paths. Then the travel path errors can be obtained by afterwards calculation. Secondly, we use SICK laser positioning system to acquire the actual position of the robot and correct path to the coordinates preset. Path planning of the robot has been a line, circle, square and S-shaped paths. Control interface is written using Visual Basic 6.0. We can send control instructions by the RS232 to USB drive to do communication with the motor. In this manner, we make the robot walk along the preset paths with minimum errors. Keywords: Path error, Restaurant service robot, Differential drive,Path planning
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Hung, Po-Chien, and 洪博謙. "Snake robot locomotion planning and analysis." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/77pnw6.
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碩士中原大學
電機工程研究所
104
Biological snakes can change locomotion depending on different environments. Therefore, biological snakes have great ability to adapt to various environments. Because this reason, snake-like robots have been developed to take this advantage, so that it can be used to rescue and explore in the unknown and complex environment. This thesis focuses on snake-like robot locomotion technique used for moving inside of nuclear power plant. Because nuclear power plant environment is very complex, it is not easy to enter and detect the pipe by using operators or large equipment. The proposed snake-like robot is constructed by ten servo motors. Serpentine and caterpillar locomotion technique are applied to move the snake. The servo motors are controlled by SSC (Serial Servo Controller), and SSC receives PWM (Pulse Width Modulation) signal as the command from a computer. The experiment results show the snake-like robot can achieve forward, right-turn and left-turn locomotion in a 6 inch pipe.