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Soft-Material Robotics
Introduces the fundamentals aspects of the topic from history, modelling, control, and system integration. The last decade has witnessed an increasing interest in the more active use of soft materials in robotic systems. Having a soft body like the ones in biological systems can potentially provide a robot with superior capabilities.
Springer Handbook of Robotics
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 o...
Factor Graphs for Robot Perception
Reviews the use of factor graphs for the modeling and solving of large-scale inference problems in robotics. Factor graphs are introduced as an economical representation within which to formulate the different inference problems, setting the stage for the subsequent sections on practical methods to solve them.
Foundations of Artificial Intelligence and Robotics
Artificial intelligence (AI) is a complicated science that combines philosophy, cognitive psychology, neuroscience, mathematics and logic (logicism), economics, computer science, computability, and software. Meanwhile, robotics is an engineering field that compliments AI. There can be situations where AI can function without a robot (e.g., Turing Test) and robotics without AI (e.g., teleoperation), but in many cases, each technology requires each other to exhibit a complete system: having "smart" robots and AI being able to control its interactions (i.e., effectors) with its environment. This book provides a complete history of computing, AI, and robotics from its early development to stateâ...
Inductive Biases in Machine Learning for Robotics and Control
One important robotics problem is “How can one program a robot to perform a task”? Classical robotics solves this problem by manually engineering modules for state estimation, planning, and control. In contrast, robot learning solely relies on black-box models and data. This book shows that these two approaches of classical engineering and black-box machine learning are not mutually exclusive. To solve tasks with robots, one can transfer insights from classical robotics to deep networks and obtain better learning algorithms for robotics and control. To highlight that incorporating existing knowledge as inductive biases in machine learning algorithms improves performance, this book covers different approaches for learning dynamics models and learning robust control policies. The presented algorithms leverage the knowledge of Newtonian Mechanics, Lagrangian Mechanics as well as the Hamilton-Jacobi-Isaacs differential equation as inductive bias and are evaluated on physical robots.
Tactile Guidance for Policy Adaptation
Demonstration learning is a powerful and practical technique to develop robot behaviors. Even so, development remains a challenge and possible demonstration limitations, for example correspondence issues between the robot and demonstrator, can degrade policy performance. This work presents an approach for policy improvement through a tactile interface located on the body of the robot. We introduce the Tactile Policy Correction (TPC) algorithm, that employs tactile feedback for the refinement of a demonstrated policy, as well as its reuse for the development of other policies. The TPC algorithm is validated on humanoid robot performing grasp positioning tasks. The performance of the demonstrated policy is found to improve with tactile corrections. Tactile guidance also is shown to enable the development of policies able to successfully execute novel, undemonstrated, tasks. We further show that different modalities, namely teleoperation and tactile control, provide information about allowable variability in the target behavior in different areas of the state space.
The De Gruyter Handbook of Robots in Society and Culture
The De Gruyter Handbook of Robots in Society and Culture provides a comprehensive discussion of how social robots take form, function, and meaning for individuals, relationships, cultures, and societies. Through a path-breaking integration of perspectives coming from sociology, communication and media, psychology, cognitive neuroscience, anthropology, political science, and science and technology studies, it focuses on the critical and social meaning of present developments in social robotic technologies. This book looks at artificial agents – from voice-based assistants to humanoid robots— as their use transforms private and public contexts and gives rise to both new possibilities and n...
Service Robots
The idea of using robots in our daily lives was an inspiring research in the field of robotics during the last decades. Service robots can be found nowadays in warehouses, hospitals, retail stores, city streets, and industrial parks or as personal assistants. The effort on the development of these robots is confirmed by the amount of money invested in projects and companies, the creation on new start-ups worldwide, and, not less important, the quantity and quality of the manuscripts published in journals and conferences worldwide. This book is an outcome of research done by several researchers who have highly contributed to the field of service robots. The main goal of this book is to present the recent advances in the field of service robots.
Computational Principles of Mobile Robotics
Now in its third edition, this textbook is a comprehensive introduction to the multidisciplinary field of mobile robotics, which lies at the intersection of artificial intelligence, computational vision, and traditional robotics. Written for advanced undergraduates and graduate students in computer science and engineering, the book covers algorithms for a range of strategies for locomotion, sensing, and reasoning. The new edition includes recent advances in robotics and intelligent machines, including coverage of human-robot interaction, robot ethics, and the application of advanced AI techniques to end-to-end robot control and specific computational tasks. This book also provides support for a number of algorithms using ROS 2, and includes a review of critical mathematical material and an extensive list of sample problems. Researchers as well as students in the field of mobile robotics will appreciate this comprehensive treatment of state-of-the-art methods and key technologies.
Robotics, Vision and Control
This textbook provides a comprehensive, but tutorial, introduction to robotics, computer vision, and control. It is written in a light but informative conversational style, weaving text, figures, mathematics, and lines of code into a cohesive narrative. Over 1600 code examples show how complex problems can be decomposed and solved using just a few simple lines of code. This edition is based on MATLAB® and a number of MathWorks® toolboxes. These provide a set of supported software tools for addressing a broad range of applications in robotics and computer vision. These toolboxes enable the reader to easily bring the algorithmic concepts into practice and work with real, non-trivial, problems. For the beginning student, the book makes the algorithms accessible, the toolbox code can be read to gain understanding, and the examples illustrate how it can be used. The code can also be the starting point for new work, for practitioners, students, or researchers, by writing programs based on toolbox functions. Two co-authors from MathWorks have joined the writing team and bring deep knowledge of these MATLAB toolboxes and workflows.
