Robot Learning From Human Demonstration

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Robot Learning from Human Teachers

Author : Sonia Chernova,Andrea L. Thomaz
Publisher : Morgan & Claypool Publishers
Page : 154 pages
File Size : 48,7 Mb
Release : 2014-04-01
Category : Computers
ISBN : 9781681731797

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Robot Learning from Human Teachers by Sonia Chernova,Andrea L. Thomaz Pdf

Learning from Demonstration (LfD) explores techniques for learning a task policy from examples provided by a human teacher. The field of LfD has grown into an extensive body of literature over the past 30 years, with a wide variety of approaches for encoding human demonstrations and modeling skills and tasks. Additionally, we have recently seen a focus on gathering data from non-expert human teachers (i.e., domain experts but not robotics experts). In this book, we provide an introduction to the field with a focus on the unique technical challenges associated with designing robots that learn from naive human teachers. We begin, in the introduction, with a unification of the various terminology seen in the literature as well as an outline of the design choices one has in designing an LfD system. Chapter 2 gives a brief survey of the psychology literature that provides insights from human social learning that are relevant to designing robotic social learners. Chapter 3 walks through an LfD interaction, surveying the design choices one makes and state of the art approaches in prior work. First, is the choice of input, how the human teacher interacts with the robot to provide demonstrations. Next, is the choice of modeling technique. Currently, there is a dichotomy in the field between approaches that model low-level motor skills and those that model high-level tasks composed of primitive actions. We devote a chapter to each of these. Chapter 7 is devoted to interactive and active learning approaches that allow the robot to refine an existing task model. And finally, Chapter 8 provides best practices for evaluation of LfD systems, with a focus on how to approach experiments with human subjects in this domain.

Robot Programming by Demonstration

Author : Sylvain Calinon
Publisher : EPFL Press
Page : 248 pages
File Size : 42,6 Mb
Release : 2009-08-24
Category : Computers
ISBN : 1439808678

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Robot Programming by Demonstration by Sylvain Calinon Pdf

Recent advances in RbD have identified a number of key issues for ensuring a generic approach to the transfer of skills across various agents and contexts. This book focuses on the two generic questions of what to imitate and how to imitate and proposes active teaching methods.

Robot Learning Human Skills and Intelligent Control Design

Author : CHENGUANG. YANG,Chao Zeng,Jianwei Zhang
Publisher : CRC Press
Page : 0 pages
File Size : 49,9 Mb
Release : 2023-09-25
Category : Electronic
ISBN : 0367634376

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Robot Learning Human Skills and Intelligent Control Design by CHENGUANG. YANG,Chao Zeng,Jianwei Zhang Pdf

This book focusses on robotic skill learning and intelligent control for robotic manipulators including enabling of robots to efficiently learn motor and stiffness/force regulation policies from humans. It explains transfer of human limb impedance control strategies to the robots so that the adaptive impedance control for the robot can be realized.

Robot Learning Human Skills and Intelligent Control Design

Author : Chenguang Yang,Chao Zeng,Jianwei Zhang
Publisher : CRC Press
Page : 184 pages
File Size : 54,7 Mb
Release : 2021-06-21
Category : Computers
ISBN : 9781000395174

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Robot Learning Human Skills and Intelligent Control Design by Chenguang Yang,Chao Zeng,Jianwei Zhang Pdf

In the last decades robots are expected to be of increasing intelligence to deal with a large range of tasks. Especially, robots are supposed to be able to learn manipulation skills from humans. To this end, a number of learning algorithms and techniques have been developed and successfully implemented for various robotic tasks. Among these methods, learning from demonstrations (LfD) enables robots to effectively and efficiently acquire skills by learning from human demonstrators, such that a robot can be quickly programmed to perform a new task. This book introduces recent results on the development of advanced LfD-based learning and control approaches to improve the robot dexterous manipulation. First, there's an introduction to the simulation tools and robot platforms used in the authors' research. In order to enable a robot learning of human-like adaptive skills, the book explains how to transfer a human user’s arm variable stiffness to the robot, based on the online estimation from the muscle electromyography (EMG). Next, the motion and impedance profiles can be both modelled by dynamical movement primitives such that both of them can be planned and generalized for new tasks. Furthermore, the book introduces how to learn the correlation between signals collected from demonstration, i.e., motion trajectory, stiffness profile estimated from EMG and interaction force, using statistical models such as hidden semi-Markov model and Gaussian Mixture Regression. Several widely used human-robot interaction interfaces (such as motion capture-based teleoperation) are presented, which allow a human user to interact with a robot and transfer movements to it in both simulation and real-word environments. Finally, improved performance of robot manipulation resulted from neural network enhanced control strategies is presented. A large number of examples of simulation and experiments of daily life tasks are included in this book to facilitate better understanding of the readers.

Learning for Adaptive and Reactive Robot Control

Author : Aude Billard,Sina Mirrazavi,Nadia Figueroa
Publisher : MIT Press
Page : 425 pages
File Size : 49,5 Mb
Release : 2022-02-08
Category : Technology & Engineering
ISBN : 9780262367011

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Learning for Adaptive and Reactive Robot Control by Aude Billard,Sina Mirrazavi,Nadia Figueroa Pdf

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.

Robot Learning by Visual Observation

Author : Aleksandar Vakanski,Farrokh Janabi-Sharifi
Publisher : John Wiley & Sons
Page : 208 pages
File Size : 40,7 Mb
Release : 2017-01-13
Category : Technology & Engineering
ISBN : 9781119091783

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Robot Learning by Visual Observation by Aleksandar Vakanski,Farrokh Janabi-Sharifi Pdf

This book presents programming by demonstration for robot learning from observations with a focus on the trajectory level of task abstraction Discusses methods for optimization of task reproduction, such as reformulation of task planning as a constrained optimization problem Focuses on regression approaches, such as Gaussian mixture regression, spline regression, and locally weighted regression Concentrates on the use of vision sensors for capturing motions and actions during task demonstration by a human task expert

Intelligent Robotics and Applications

Author : Zhiyong Chen,Alexandre Mendes,Yamin Yan,Shifeng Chen
Publisher : Springer
Page : 501 pages
File Size : 51,5 Mb
Release : 2018-08-02
Category : Computers
ISBN : 9783319975863

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Intelligent Robotics and Applications by Zhiyong Chen,Alexandre Mendes,Yamin Yan,Shifeng Chen Pdf

The two volume set LNAI 10984 and LNAI 10985 constitutes the refereed proceedings of the 11th International Conference on Intelligent Robotics and Applications, ICIRA 2018, held in Newcastle, NSW, Australia, in August 2018. The 81 papers presented in the two volumes were carefully reviewed and selected from 129 submissions. The papers in the first volume of the set are organized in topical sections on multi-agent systems and distributed control; human-machine interaction; rehabilitation robotics; sensors and actuators; and industrial robot and robot manufacturing. The papers in the second volume of the set are organized in topical sections on robot grasping and control; mobile robotics and path planning; robotic vision, recognition and reconstruction; and robot intelligence and learning.

Robotics Research

Author : John M. Hollerbach,Daniel E. Koditscheck
Publisher : Springer Science & Business Media
Page : 443 pages
File Size : 54,8 Mb
Release : 2012-12-06
Category : Technology & Engineering
ISBN : 9781447107651

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Robotics Research by John M. Hollerbach,Daniel E. Koditscheck Pdf

This book is the proceedings of the 9th International Symposium of Robotics Research, one of the oldest and most prestigious conferences in robotics. The goal of the symposium was to bring together active, leading robotics researchers from academia, government and industry, to define the state of the art of robotics and its future direction. The broad spectrum of robotics research is covered, with an eye on what will be important in robotics in the next millennium.

Wearable Technology for Robotic Manipulation and Learning

Author : Bin Fang,Fuchun Sun,Huaping Liu,Chunfang Liu,Di Guo
Publisher : Springer Nature
Page : 219 pages
File Size : 47,6 Mb
Release : 2020-10-06
Category : Technology & Engineering
ISBN : 9789811551246

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Wearable Technology for Robotic Manipulation and Learning by Bin Fang,Fuchun Sun,Huaping Liu,Chunfang Liu,Di Guo Pdf

Over the next few decades, millions of people, with varying backgrounds and levels of technical expertise, will have to effectively interact with robotic technologies on a daily basis. This means it will have to be possible to modify robot behavior without explicitly writing code, but instead via a small number of wearable devices or visual demonstrations. At the same time, robots will need to infer and predict humans’ intentions and internal objectives on the basis of past interactions in order to provide assistance before it is explicitly requested; this is the basis of imitation learning for robotics. This book introduces readers to robotic imitation learning based on human demonstration with wearable devices. It presents an advanced calibration method for wearable sensors and fusion approaches under the Kalman filter framework, as well as a novel wearable device for capturing gestures and other motions. Furthermore it describes the wearable-device-based and vision-based imitation learning method for robotic manipulation, making it a valuable reference guide for graduate students with a basic knowledge of machine learning, and for researchers interested in wearable computing and robotic learning.

Designing Robot Behavior in Human-Robot Interactions

Author : Changliu Liu,Te Tang,Hsien-Chung Lin,Masayoshi Tomizuka
Publisher : CRC Press
Page : 206 pages
File Size : 50,8 Mb
Release : 2019-09-12
Category : Computers
ISBN : 9780429602856

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Designing Robot Behavior in Human-Robot Interactions by Changliu Liu,Te Tang,Hsien-Chung Lin,Masayoshi Tomizuka Pdf

In this book, we have set up a unified analytical framework for various human-robot systems, which involve peer-peer interactions (either space-sharing or time-sharing) or hierarchical interactions. A methodology in designing the robot behavior through control, planning, decision and learning is proposed. In particular, the following topics are discussed in-depth: safety during human-robot interactions, efficiency in real-time robot motion planning, imitation of human behaviors from demonstration, dexterity of robots to adapt to different environments and tasks, cooperation among robots and humans with conflict resolution. These methods are applied in various scenarios, such as human-robot collaborative assembly, robot skill learning from human demonstration, interaction between autonomous and human-driven vehicles, etc. Key Features: Proposes a unified framework to model and analyze human-robot interactions under different modes of interactions. Systematically discusses the control, decision and learning algorithms to enable robots to interact safely with humans in a variety of applications. Presents numerous experimental studies with both industrial collaborative robot arms and autonomous vehicles.

An Algorithmic Perspective on Imitation Learning

Author : Takayuki Osa,Joni Pajarinen,Gerhard Neumann,J. Andrew Bagnell,Pieter Abbeel,Jan Peters
Publisher : Unknown
Page : 194 pages
File Size : 43,7 Mb
Release : 2018-03-27
Category : Technology & Engineering
ISBN : 168083410X

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An Algorithmic Perspective on Imitation Learning by Takayuki Osa,Joni Pajarinen,Gerhard Neumann,J. Andrew Bagnell,Pieter Abbeel,Jan Peters Pdf

Familiarizes machine learning experts with imitation learning, statistical supervised learning theory, and reinforcement learning. It also roboticists and experts in applied artificial intelligence with a broader appreciation for the frameworks and tools available for imitation learning.

Robot Learning from Human Demonstration

Author : Sonia Dechter,Andrea L. Haslum
Publisher : Springer Nature
Page : 109 pages
File Size : 48,8 Mb
Release : 2022-06-01
Category : Computers
ISBN : 9783031015700

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Robot Learning from Human Demonstration by Sonia Dechter,Andrea L. Haslum Pdf

Learning from Demonstration (LfD) explores techniques for learning a task policy from examples provided by a human teacher. The field of LfD has grown into an extensive body of literature over the past 30 years, with a wide variety of approaches for encoding human demonstrations and modeling skills and tasks. Additionally, we have recently seen a focus on gathering data from non-expert human teachers (i.e., domain experts but not robotics experts). In this book, we provide an introduction to the field with a focus on the unique technical challenges associated with designing robots that learn from naive human teachers. We begin, in the introduction, with a unification of the various terminology seen in the literature as well as an outline of the design choices one has in designing an LfD system. Chapter 2 gives a brief survey of the psychology literature that provides insights from human social learning that are relevant to designing robotic social learners. Chapter 3 walks through an LfD interaction, surveying the design choices one makes and state of the art approaches in prior work. First, is the choice of input, how the human teacher interacts with the robot to provide demonstrations. Next, is the choice of modeling technique. Currently, there is a dichotomy in the field between approaches that model low-level motor skills and those that model high-level tasks composed of primitive actions. We devote a chapter to each of these. Chapter 7 is devoted to interactive and active learning approaches that allow the robot to refine an existing task model. And finally, Chapter 8 provides best practices for evaluation of LfD systems, with a focus on how to approach experiments with human subjects in this domain.

Approaches to Probabilistic Model Learning for Mobile Manipulation Robots

Author : Jürgen Sturm
Publisher : Springer
Page : 204 pages
File Size : 51,6 Mb
Release : 2013-12-12
Category : Technology & Engineering
ISBN : 9783642371608

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Approaches to Probabilistic Model Learning for Mobile Manipulation Robots by Jürgen Sturm Pdf

This book presents techniques that enable mobile manipulation robots to autonomously adapt to new situations. Covers kinematic modeling and learning; self-calibration; tactile sensing and object recognition; imitation learning and programming by demonstration.

Human-robot Interaction

Author : Michael A. Goodrich,Alan C. Schultz
Publisher : Now Publishers Inc
Page : 89 pages
File Size : 45,5 Mb
Release : 2007
Category : Computers
ISBN : 9781601980922

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Human-robot Interaction by Michael A. Goodrich,Alan C. Schultz Pdf

Presents a unified treatment of HRI-related issues, identifies key themes, and discusses challenge problems that are likely to shape the field in the near future. The survey includes research results from a cross section of the universities, government efforts, industry labs, and countries that contribute to HRI.

Springer Handbook of Robotics

Author : Bruno Siciliano,Oussama Khatib
Publisher : Springer
Page : 2259 pages
File Size : 46,9 Mb
Release : 2016-07-27
Category : Technology & Engineering
ISBN : 9783319325521

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Springer Handbook of Robotics by Bruno Siciliano,Oussama Khatib Pdf

The second edition of this handbook provides a state-of-the-art overview on the various aspects in the rapidly developing field of robotics. Reaching for the human frontier, robotics is vigorously engaged in the growing challenges of new emerging domains. Interacting, exploring, and working with humans, the new generation of robots will increasingly touch people and their lives. The credible prospect of practical robots among humans is the result of the scientific endeavour of a half a century of robotic developments that established robotics as a modern scientific discipline. The ongoing vibrant expansion and strong growth of the field during the last decade has fueled this second edition of the Springer Handbook of Robotics. The first edition of the handbook soon became a landmark in robotics publishing and won the American Association of Publishers PROSE Award for Excellence in Physical Sciences & Mathematics as well as the organization’s Award for Engineering & Technology. The second edition of the handbook, edited by two internationally renowned scientists with the support of an outstanding team of seven part editors and more than 200 authors, continues to be an authoritative reference for robotics researchers, newcomers to the field, and scholars from related disciplines. The contents have been restructured to achieve four main objectives: the enlargement of foundational topics for robotics, the enlightenment of design of various types of robotic systems, the extension of the treatment on robots moving in the environment, and the enrichment of advanced robotics applications. Further to an extensive update, fifteen new chapters have been introduced on emerging topics, and a new generation of authors have joined the handbook’s team. A novel addition to the second edition is a comprehensive collection of multimedia references to more than 700 videos, which bring valuable insight into the contents. The videos can be viewed directly augmented into the text with a smartphone or tablet using a unique and specially designed app. Springer Handbook of Robotics Multimedia Extension Portal: http://handbookofrobotics.org/