This book introduces a novel model-based dexterous manipulation framework, which, thanks to its precision and versatility, significantly advances the capabilities of robotic hands compared to the previous state of the art. This is achieved by combining a novel grasp state estimation algorithm, the first to integrate information from tactile sensing, proprioception and vision, with an impedance-based in-hand object controller, which enables leading manipulation capabilities, including finger gaiting. The developed concept is implemented on one of the most advanced robotic manipulators, the DLR humanoid robot David, and evaluated in a range of challenging real-world manipulation scenarios and tasks. This book greatly benefits researchers in the field of robotics that study robotic hands and dexterous manipulation topics, as well as developers and engineers working on industrial automation applications involving grippers and robotic manipulators.

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

These 16 contributions provide a field guide to robotics science today.These 16 contributions provide a field guide to robotics science today. Each takes up current work the problems addressed, and future directions in the areas of perception, planning, control, design, and actuation. In a substantial introduction, Michael Brady summarizes a personal list of 30 problems, problem areas, and issues that lie on the path to development of a science of robotics. These involve sensing vision, mobility, design, control, manipulation, reasoning, geometric reasoning and systems integration.ContentsThe Problems of Robotics, Michael Brady - Perception. A Few Steps Toward Artificial 3-D Vision, Olivier D. Faugeras - Contact Sensing for Robot Active Touch, Paolo Dario - Learning and Recognition in Natural Environments, Alex Pentland and Robert Bolles - 3-D Vision for Outdoor Navigation by an Autonomous Vehicle, Martial Hebert and Takeo Kanade - Planning. Geometric Issues in Planning Robot Tasks, Tomas Lozano Perez and Russell Taylor - Robotic Manipulation: Mechanics and Planning, Matthew Mason - Control. A Survey of Manipulation and Assembly: Development of the Field and Open Research Issues, Daniel Whitney - Control, Suguru Arimoto - Kinematics and Dynamics for Control, John Hollerbach - The Whole Iguana, Rodney Brooks - Design and Actuation. Design and Kinematics for Force and Velocity Control of Manipulators and End Effectors, Bernard Roth - Arm Design, Haruhiko Asada - Behavior Based Design of Robot Effectors, Stephen Jacobsen, Craig Smith, Klaus Biggers, and Edwin Iversen - Using an Articulated Hand to Manipulate Objects, Kenneth Salisbury, David Brock and Patrick O'Donnell - Legged Robots, Marc RaibertRobotics Science is included in the System Development Foundation Benchmark series. System Development Foundation grants have contributed significantly to the development of robotics in the United States during the 1980s.

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. - Investigates current research direction in robotic manipulation - Shows how human manipulation techniques and skills can be transferred to robotic manipulation - Identifies key human hand structures for robotic hand design and how they should be embedded in the robotic hand for dexterous manipulation

“The Human Hand as an Inspiration for Robot Hand Development” presents an edited collection of authoritative contributions in the area of robot hands. The results described in the volume are expected to lead to more robust, dependable, and inexpensive distributed systems such as those endowed with complex and advanced sensing, actuation, computation, and communication capabilities. The twenty-four chapters discuss the field of robotic grasping and manipulation viewed in light of the human hand’s capabilities and push the state-of-the-art in robot hand design and control. Topics discussed include human hand biomechanics, neural control, sensory feedback and perception, and robotic grasp and manipulation. This book will be useful for researchers from diverse areas such as robotics, biomechanics, neuroscience, and anthropologists.

This book looks at the common problems both human and robotic hands encounter when controlling the large number of joints, actuators and sensors required to efficiently perform motor tasks such as object exploration, manipulation and grasping. The authors adopt an integrated approach to explore the control of the hand based on sensorimotor synergies that can be applied in both neuroscience and robotics. Hand synergies are based on goal-directed, combined muscle and kinematic activation leading to a reduction of the dimensionality of the motor and sensory space, presenting a highly effective solution for the fast and simplified design of artificial systems. Presented in two parts, the first part, Neuroscience, provides the theoretical and experimental foundations to describe the synergistic organization of the human hand. The second part, Robotics, Models and Sensing Tools, exploits the framework of hand synergies to better control and design robotic hands and haptic/sensing systems/tools, using a reduced number of control inputs/sensors, with the goal of pushing their effectiveness close to the natural one. Human and Robot Hands provides a valuable reference for students, researchers and designers who are interested in the study and design of the artificial hand.