Robot Learning Human Skills and Intelligent Control Design PDF Download

Author: CHENGUANG. YANG
Publisher: CRC Press
ISBN: 9780367634377
Category :
Languages : en
Pages : 0

View

Book Description
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.

Author: Qiang Li
Publisher: Academic Press
ISBN: 0323904173
Category : Computers
Languages : en
Pages : 374

View

Book Description
Tactile Sensing, Skill Learning and Robotic Dexterous Manipulation focuses on cross-disciplinary lines of research and groundbreaking research ideas in three research lines: tactile sensing, skill learning and dexterous control. The book introduces recent work about human dexterous skill representation and learning, along with discussions of tactile sensing and its applications on unknown objects' property recognition and reconstruction. Sections also introduce the adaptive control schema and its learning by imitation and exploration. Other chapters describe the fundamental part of relevant research, paying attention to the connection among different fields and showing the state-of-the-art in related branches. The book summarizes the different approaches and discusses the pros and cons of each. Chapters not only describe the research but also include basic knowledge that can help readers understand the proposed work, making it an excellent resource for researchers and professionals who work in the robotics industry, haptics and in machine learning. - Provides a review of tactile perception and the latest advances in the use of robotic dexterous manipulation - Presents the most detailed work on synthesizing intelligent tactile perception, skill learning and adaptive control - Introduces recent work on human's dexterous skill representation and learning and the adaptive control schema and its learning by imitation and exploration - Reveals and illustrates how robots can improve dexterity by modern tactile sensing, interactive perception, learning and adaptive control approaches

Author: Tetsuyou Watanabe
Publisher: Academic Press
ISBN: 9780128133859
Category : Technology & Engineering
Languages : en
Pages : 0

View

Book Description
Human Inspired Dexterity in Robotic Manipulation provides up-to-date research and information on how to imitate humans and realize robotic manipulation. Approaches from both software and hardware viewpoints are shown, with sections discussing, and highlighting, case studies that demonstrate how human manipulation techniques or skills can be transferred to robotic manipulation. From the hardware viewpoint, the book discusses important human hand structures that are key for robotic hand design and how they should be embedded for dexterous manipulation. This book is ideal for the research communities in robotics, mechatronics and automation.

Author: Aude Billard
Publisher: MIT Press
ISBN: 0262367017
Category : Technology & Engineering
Languages : en
Pages : 425

View

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: Francis X. Govers
Publisher: Packt Publishing Ltd
ISBN: 1788835700
Category : Computers
Languages : en
Pages : 336

View

Book Description
Bring a new degree of interconnectivity to your world by building your own intelligent robots Key Features Leverage fundamentals of AI and robotics Work through use cases to implement various machine learning algorithms Explore Natural Language Processing (NLP) concepts for efficient decision making in robots Book DescriptionArtificial Intelligence for Robotics starts with an introduction to Robot Operating Systems (ROS), Python, robotic fundamentals, and the software and tools that are required to start out with robotics. You will learn robotics concepts that will be useful for making decisions, along with basic navigation skills. As you make your way through the chapters, you will learn about object recognition and genetic algorithms, which will teach your robot to identify and pick up an irregular object. With plenty of use cases throughout, you will explore natural language processing (NLP) and machine learning techniques to further enhance your robot. In the concluding chapters, you will learn about path planning and goal-oriented programming, which will help your robot prioritize tasks. By the end of this book, you will have learned to give your robot an artificial personality using simulated intelligence.What you will learn Get started with robotics and artificial intelligence Apply simulation techniques to give your robot an artificial personality Understand object recognition using neural networks and supervised learning techniques Pick up objects using genetic algorithms for manipulation Teach your robot to listen using NLP via an expert system Use machine learning and computer vision to teach your robot how to avoid obstacles Understand path planning, decision trees, and search algorithms in order to enhance your robot Who this book is for If you have basic knowledge about robotics and want to build or enhance your existing robot’s intelligence, then Artificial Intelligence for Robotics is for you. This book is also for enthusiasts who want to gain knowledge of AI and robotics.

Author: Sylvain Calinon
Publisher: EPFL Press
ISBN: 9781439808672
Category : Computers
Languages : en
Pages : 248

View

Book Description
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.

Author: Bruno Siciliano
Publisher: Springer Science & Business Media
ISBN: 364229040X
Category : Computers
Languages : en
Pages : 284

View

Book Description
Dexterous and autonomous manipulation is a key technology for the personal and service robots of the future. Advances in Bimanual Manipulation edited by Bruno Siciliano provides the robotics community with the most noticeable results of the four-year European project DEXMART (DEXterous and autonomous dual-arm hand robotic manipulation with sMART sensory-motor skills: A bridge from natural to artificial cognition). The volume covers a host of highly important topics in the field, concerned with modelling and learning of human manipulation skills, algorithms for task planning, human-robot interaction, and grasping, as well as hardware design of dexterous anthropomorphic hands. The results described in this five-chapter collection are believed to pave the way towards the development of robotic systems endowed with dexterous and human-aware dual-arm/hand manipulation skills for objects, operating with a high degree of autonomy in unstructured real-world environments.

Author: Arash Ajoudani
Publisher: Springer
ISBN: 3319242059
Category : Technology & Engineering
Languages : en
Pages : 180

View

Book Description
This book introduces novel thinking and techniques to the control of robotic manipulation. In particular, the concept of teleimpedance control as an alternative method to bilateral force-reflecting teleoperation control for robotic manipulation is introduced. In teleimpedance control, a compound reference command is sent to the slave robot including both the desired motion trajectory and impedance profile, which are then realized by the remote controller. This concept forms a basis for the development of the controllers for a robotic arm, a dual-arm setup, a synergy-driven robotic hand, and a compliant exoskeleton for improved interaction performance.

Author: Matteo Bianchi
Publisher: Frontiers Media SA
ISBN: 2889457958
Category :
Languages : en
Pages : 134

View

Book Description
Humans are endowed with extraordinary sensory-motor capabilities that enable a successful interaction with and exploration of the environment, as is the case of human manipulation. Understanding and modeling these capabilities represents an important topic not only for neuroscience but also for robotics in a mutual inspiration, both to inform the design and control of artificial systems and, at the same time, to increase knowledge on the biological side. Within this context, synergies -- i.e., goal-directed actions that constrain multi DOFs of the human body and can be defined at the kinematic, muscular, neural level -- have gained increasing attention as a general simplified approach to shape the development of simple and effective artificial devices. The execution of such purposeful sensory-motor primitives on the biological side leverages on the interplay of the sensory-motor control at central and peripheral level, and the interaction of the human body with the external world. This interaction is particularly important considering the new concept of robotic soft manipulation, i.e. soft, adaptable yet robust robotic hands that can deform with the external environment to multiply their grasping and manipulation capabilities. Under this regard, a preeminent role is reserved to touch, being that skin isour primary organ to shape our knowledge of the external world and, hence, to modify it, in interaction with the efferent parts. This Research Topic reports results on the mutual inspiration between neuroscience and robotics, and on how it is possible to translate neuroscientific findings on human manipulation into engineering guidelines for simplified systems able to take full advantage from the interaction and hence exploitation of environmental constraints for task accomplishment and knowledge acquisition.

Author: Leslie Pack Kaelbling
Publisher: MIT Press
ISBN: 9780262111744
Category : Computers
Languages : en
Pages : 206

View

Book Description
Learning to perform complex action strategies is an important problem in the fields of artificial intelligence, robotics and machine learning. Presenting interesting, new experimental results, Learning in Embedded Systems explores algorithms that learn efficiently from trial and error experience with an external world. The text is a detailed exploration of the problem of learning action strategies in the context of designing embedded systems that adapt their behaviour to a complex, changing environment. Such systems include mobile robots, factory process controllers and long-term software databases.