Tactile Sensing, Skill Learning, and Robotic Dexterous Manipulation

Tactile Sensing, Skill Learning and Robotic Dexterous Manipulation focuses on the cross-disciplinary lines of research and ground-breaking research ideas on three research lines: tactile sensing, skill learning and dexterous control. The book introduces the recent work about human’s dexterous skill representation and learning; tactile sensing and its applications on unknown objects’ property recognition and reconstruction. It also introduces the adaptive control schema and its learning by imitation and exploration. The book describes the fundamental part of relevant research, paying attention to the connection among different fields and showing the state-of-the-art in the related branches. The book summarizes the different approaches and discusses the pros and cons of each, and the chapters not only describe the research but also include basic knowledge which can help readers to understand the proposed work. It also gives insight into recent representative results from different research branches, a whole picture about the state-of-the-art and potential future research directions for robotic dexterous manipulation. It reveals and illustrates how robots can improve its dexterity by modern tactile sensing, interactive perception, learning and adaptive control approaches. This book is an excellent resource for researchers and professionals who work in the robotics industry, haptics and machine learning. Provides a review of tactile perception and latest advances in the use of robotic dexterous manipulation Provides the most detailed work on synthesizing intelligent tactile perception, skill learning and adaptive control Introduces the recent work on human’s dexterous skill representation and learning, the adaptive control schema and its learning by imitation and exploration and the adaptive control schema and its learning by imitation and exploration Reveals and illustrates how robots can improve its dexterity by modern tactile sensing, interactive perception, learning and adaptive control approaches