Human Like Advances In Robotics Motion Actuation Sensing Cognition And Control

Humanoid robots are highly sophisticated machines equipped with human-like sensory and motor capabilities. Today we are on the verge of a new era of rapid transformations in both science and engineering-one that brings together technological advancements in a way that will accelerate both neuroscience and robotics. Humanoid Robotics and Neuroscienc

Research on humanoid robots has been mostly with the aim of developing robots that can replace humans in the performance of certain tasks. Motion planning for these robots can be quite difficult, due to their complex kinematics, dynamics and environment. It is consequently one of the key research topics in humanoid robotics research and the last few years have witnessed considerable progress in the field. Motion Planning for Humanoid Robots surveys the remarkable recent advancement in both the theoretical and the practical aspects of humanoid motion planning. Various motion planning frameworks are presented in Motion Planning for Humanoid Robots, including one for skill coordination and learning, and one for manipulating and grasping tasks. The problem of planning sequences of contacts that support acyclic motion in a highly constrained environment is addressed and a motion planner that enables a humanoid robot to push an object to a desired location on a cluttered table is described. The main areas of interest include: • whole body motion planning, • task planning, • biped gait planning, and • sensor feedback for motion planning. Torque-level control of multi-contact behavior, autonomous manipulation of moving obstacles, and movement control and planning architecture are also covered. Motion Planning for Humanoid Robots will help readers to understand the current research on humanoid motion planning. It is written for industrial engineers, advanced undergraduate and postgraduate students.

A leap forward in the field of robotics Until now, most of the advances in robotics have taken place instructured environments. Scientists and engineers have designedhighly sophisticated robots, but most are still only able tooperate and move in predetermined, planned environments designedspecifically for the robots and typically at very high cost. Thisnew book takes robotics to the next level by setting forth thetheory and techniques needed to achieve robotic motion inunstructured environments. The ability to move and operate in anarbitrary, unplanned environment will lead to automating a widerange of new robotic tasks, such as patient care, toxic sitecleanup, and planetary exploration. The approach that opens the door for robots to handle unstructuredtasks is known as Sensing-Intelligence-Motion (SIM), which drawsfrom research in topology, computational complexity, controltheory, and sensing hardware. Using SIM as an underlyingfoundation, the author's carefully structured presentation isdesigned to: * Formulate the challenges of sensor-based motion planning and thenbuild a theoretical foundation for sensor-based motion planningstrategies * Investigate promising algorithmic strategies for mobile robotsand robot arm manipulators, in both cases addressing motionplanning for the whole robot body * Compare robot performance to human performance in sensor-basedmotion planning to gain better insight into the challenges of SIMand help build synergistic human-robot teams for tele-operationtasks. It is both exciting and encouraging to discover that robotperformance decisively exceeds human performance in certain tasksrequiring spatial reasoning, even when compared to trainedoperators * Review sensing hardware that is necessary to realize the SIMparadigm Some 200 illustrations, graphic sketches, and photos are includedto clarify key issues, develop and validate motion planningapproaches, and demonstrate full systems in operation. As the first book fully devoted to robot motion planning inunstructured environments, Sensing, Intelligence, Motion is amust-read for engineers, scientists, and researchers involved inrobotics. It will help them migrate robots from highly specializedapplications in factories to widespread use in society whereautonomous robot motion is needed.

This volume surveys three decades of modern robot control theory and describes how the work of Suguru Arimoto shaped its development. Twelve survey articles written by experts associated with Suguru Arimoto at various stages in his career treat the subject comprehensively. This book provides an important reference for graduate students and researchers, as well as for mathematicians, engineers and scientists whose work involves robot control theory.

This book investigates a biologically inspired method of robot arm control, developed with the objective of synthesising human-like motion dynamically, using nonlinear, robust and adaptive control techniques in practical robot systems. The control method caters to a rising interest in humanoid robots and the need for appropriate control schemes to match these systems. Unlike the classic kinematic schemes used in industrial manipulators, the dynamic approaches proposed here promote human-like motion with better exploitation of the robot’s physical structure. This also benefits human-robot interaction. The control schemes proposed in this book are inspired by a wealth of human-motion literature that indicates the drivers of motion to be dynamic, model-based and optimal. Such considerations lend themselves nicely to achievement via nonlinear control techniques without the necessity for extensive and complex biological models. The operational-space method of robot control forms the basis of many of the techniques investigated in this book. The method includes attractive features such as the decoupling of motion into task and posture components. Various developments are made in each of these elements. Simple cost functions inspired by biomechanical “effort” and “discomfort” generate realistic posture motion. Sliding-mode techniques overcome robustness shortcomings for practical implementation. Arm compliance is achieved via a method of model-free adaptive control that also deals with actuator saturation via anti-windup compensation. A neural-network-centered learning-by-observation scheme generates new task motions, based on motion-capture data recorded from human volunteers. In other parts of the book, motion capture is used to test theories of human movement. All developed controllers are applied to the reaching motion of a humanoid robot arm and are demonstrated to be practically realisable. This book is designed to be of interest to those wishing to achieve dynamics-based human-like robot-arm motion in academic research, advanced study or certain industrial environments. The book provides motivations, extensive reviews, research results and detailed explanations. It is not only suited to practising control engineers, but also applicable for general roboticists who wish to develop control systems expertise in this area.

This book moves from a thorough investigation of human capabilities during movements and interactions with objects and environment and translates those principles into the design planning and control of innovative mechatronic systems, providing significant advancements in the fields of human–robot interaction, autonomous robots, prosthetics and assistive devices. The work presented in this monograph is characterized by a significant paradigmatic shift with respect to typical approaches, as it always place the human at the center of the technology developed, and the human represents the starting point and the actual beneficiary of the developed solutions. The content of this book is targeted to robotics and neuroscience enthusiasts, researchers and makers, students and simple lovers of the matter.

Nowadays, multiple attention have been paid on a robot working in the human living environment, such as in the field of medical, welfare, entertainment and so on. Various types of researches are being conducted actively in a variety of fields such as artificial intelligence, cognitive engineering, sensor- technology, interfaces and motion control. In the future, it is expected to realize super high functional human-like robot by integrating technologies in various fields including these types of researches. The book represents new developments and advances in the field of bio-inspired robotics research introducing the state of the art, the idea of multi-locomotion robotic system to implement the diversity of animal motion. It covers theoretical and computational aspects of Passive Dynamic Autonomous Control (PDAC), robot motion control, multi legged walking and climbing as well as brachiation focusing concrete robot systems, components and applications. In addition, gorilla type robot systems are described as hardware of Multi-Locomotion Robotic system. It is useful for students and researchers in the field of robotics in general, bio-inspired robots, multi-modal locomotion, legged walking, motion control, and humanoid robots. Furthermore, it is also of interest for lecturers and engineers in practice building systems cooperating with humans.