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Author: Luke A. Fraser
Publisher:
ISBN:
Category : Electronic books
Languages : en
Pages : 78
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Book Description
Robot tasks for real-world applications typically involve multiple paths of execution, where the same task can be achieved in different ways. This poses challenges with respect to the representation and execution of such tasks, as enumerating all possible execution paths leads to combinatorial increases in the size of the representation. We present a novel robot control architecture that addresses these challenges. The architecture 1) provides an efficient, compact encoding of tasks with multiple paths of execution, 2) uses the same compact representation as the controller that the robot will use to achieve its goals, 3) allows the robot to dynamically decide which execution path to follow using an activation spreading mechanism that relies on environmental conditions, and 4) provides a mechanism for robustness to changes in the environment during the task execution. We validate our architecture using a humanoid PR2 robot, showing that the robot dynamically selects a path of execution based on the current state of the environment, and is robust to environmental changes.
Author: Luke A. Fraser
Publisher:
ISBN:
Category : Electronic books
Languages : en
Pages : 78
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Book Description
Robot tasks for real-world applications typically involve multiple paths of execution, where the same task can be achieved in different ways. This poses challenges with respect to the representation and execution of such tasks, as enumerating all possible execution paths leads to combinatorial increases in the size of the representation. We present a novel robot control architecture that addresses these challenges. The architecture 1) provides an efficient, compact encoding of tasks with multiple paths of execution, 2) uses the same compact representation as the controller that the robot will use to achieve its goals, 3) allows the robot to dynamically decide which execution path to follow using an activation spreading mechanism that relies on environmental conditions, and 4) provides a mechanism for robustness to changes in the environment during the task execution. We validate our architecture using a humanoid PR2 robot, showing that the robot dynamically selects a path of execution based on the current state of the environment, and is robust to environmental changes.
Author: Anthony J. Barbera
Publisher:
ISBN:
Category : Robots
Languages : en
Pages : 644
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Book Description
Author: Anthony J. Barbera
Publisher:
ISBN:
Category : Robots
Languages : en
Pages : 252
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Book Description
Author: Matthew D. Knudson
Publisher:
ISBN:
Category : Adaptive control systems
Languages : en
Pages : 166
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Book Description
Coordinating multiple robots to achieve a complex task requires solving two distinct control problems: the high-level control problem of ensuring that each robot aims to perform a useful task (e.g., coordination) and the low-level control problem of ensuring that each robot actually performs the correct actions to achieve its task (e.g., navigation and locomotion). Though addressing both problems simultaneously with one algorithm is appealing, this is often difficult to impossible in domains requiring a combination of complex actions (goal selection, navigation, obstacle avoidance). This thesis establishes a hierarchical control structure, presents an adaptive navigation method, compares it to reactive navigation, and applies established adaptive coordination techniques under severe restrictions. The development and experimentation process produced results showing the following: 1) Hierarchical control structure proves effective and useful for use on resource limited robotic platforms allowing the subsequent navigation and coordination analyses to be addressed individually. 2) Adaptive navigation is an effective approach for dense environments with limited and noisy sensing, providing improvement over reactive navigation by up to 75%. 3) The application of an abstract difference objective function to training for coordination remains effective under limited information and physical robot motion restrictions, outperforming traditional system or local objectives by up to 50%. Specifically, this work establishes that neuro-evolutionary methods are applicable and beneficial both for the discovery of successful navigation techniques, as well as for the generation of coordination behavior in realistic multi-robot teams where individuals are strongly limited in sensing, communication, and computational ability. Possible extensions include increased levels of communication among individuals as well as configuring individual sensing abilities for heterogeneous teams.
Author: Anthony J. Barbera
Publisher:
ISBN:
Category : Robots
Languages : en
Pages : 242
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Book Description
Author: Joyjit Mukherjee
Publisher: Springer Nature
ISBN: 3030714608
Category : Technology & Engineering
Languages : en
Pages : 179
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Book Description
This book shows how a conventional multi-layered approach can be used to control a snake robot on a desired path while moving on a flat surface. To achieve robustness to unknown variations in surface conditions, it explores various adaptive robust control methods. The authors propose a sliding-mode control approach designed to achieve robust maneuvering for bounded uncertainty with a known upper bound. The control is modified by addition of an adaptation law to alleviate the overestimation problem of the switching gain as well as to circumvent the requirement for knowledge regarding the bounds of uncertainty. The book works toward non-conservativeness, achieving efficient tracking in the presence of slowly varying uncertainties with a specially designed framework for time-delayed control. It shows readers how to extract superior performance from their snake robots with an approach that allows robustness toward bounded time-delayed estimation errors. The book also demonstrates how the multi-layered control framework can be simplified by employing differential flatness for such a system. Finally, the mathematical model of a snake robot moving inside a uniform channel using only side-wall contact is discussed. The model has further been employed to demonstrate adaptive robust control design for such a motion. Using numerous illustrations and tables, Adaptive Robust Control for Planar Snake Robots will interest researchers, practicing engineers and postgraduate students working in the field of robotics and control systems.
Author: Fouad Sabry
Publisher: One Billion Knowledgeable
ISBN:
Category : Computers
Languages : en
Pages : 81
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Book Description
What Is Hierarchical Control System A hierarchical control system, often known as an HCS, is a type of control system that organizes the devices under its command and the software that governs them in the shape of a tree structure. When a computer network is used to implement the tree's links, the hierarchical control system in question is also a sort of networked control system. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Hierarchical Control System Chapter 2: Subsumption Architecture Chapter 3: James S. Albus Chapter 4: Cognitive Architecture Chapter 5: Intelligent Agent Chapter 6: Hybrid Intelligent System Chapter 7: Procedural Reasoning System Chapter 8: Real-time Control System Software Chapter 9: 4D-RCS Reference Model Architecture Chapter 10: Situated Approach (Artificial Intelligence) (II) Answering the public top questions about hierarchical control system. (III) Real world examples for the usage of hierarchical control system in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of hierarchical control system' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of hierarchical control system.
Author: Aude Billard
Publisher: MIT Press
ISBN: 0262367017
Category : Technology & Engineering
Languages : en
Pages : 425
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Book Description
Methods by which robots can learn control laws that enable real-time reactivity using dynamical systems; with applications and exercises. This book presents a wealth of machine learning techniques to make the control of robots more flexible and safe when interacting with humans. It introduces a set of control laws that enable reactivity using dynamical systems, a widely used method for solving motion-planning problems in robotics. These control approaches can replan in milliseconds to adapt to new environmental constraints and offer safe and compliant control of forces in contact. The techniques offer theoretical advantages, including convergence to a goal, non-penetration of obstacles, and passivity. The coverage of learning begins with low-level control parameters and progresses to higher-level competencies composed of combinations of skills. Learning for Adaptive and Reactive Robot Control is designed for graduate-level courses in robotics, with chapters that proceed from fundamentals to more advanced content. Techniques covered include learning from demonstration, optimization, and reinforcement learning, and using dynamical systems in learning control laws, trajectory planning, and methods for compliant and force control . Features for teaching in each chapter: applications, which range from arm manipulators to whole-body control of humanoid robots; pencil-and-paper and programming exercises; lecture videos, slides, and MATLAB code examples available on the author’s website . an eTextbook platform website offering protected material[EPS2] for instructors including solutions.
Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 988
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Book Description
Author: Adriano A. G. Siqueira
Publisher: Springer Science & Business Media
ISBN: 0857298984
Category : Technology & Engineering
Languages : en
Pages : 234
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Book Description
Robust Control of Robots bridges the gap between robust control theory and applications, with a special focus on robotic manipulators. It is divided into three parts: robust control of regular, fully-actuated robotic manipulators; robust post-failure control of robotic manipulators; and robust control of cooperative robotic manipulators. In each chapter the mathematical concepts are illustrated with experimental results obtained with a two-manipulator system. They are presented in enough detail to allow readers to implement the concepts in their own systems, or in Control Environment for Robots, a MATLAB®-based simulation program freely available from the authors. The target audience for Robust Control of Robots includes researchers, practicing engineers, and graduate students interested in implementing robust and fault tolerant control methodologies to robotic manipulators.
