LEADER 00000nam a2200505 i 4500 
001    978-3-319-30160-0 
003    DE-He213 
005    20161019115518.0 
006    m     o  d         
007    cr nn 008maaau 
008    160519s2016    gw      s         0 eng d 
020    9783319301600|q(electronic bk.) 
020    9783319301587|q(paper) 
024 7  10.1007/978-3-319-30160-0|2doi 
040    GP|cGP|erda|dAS 
041 0  eng 
050  4 TJ211.35 
082 04 629.8|223 
100 1  Spiers, Adam,|eauthor 
245 10 Biologically inspired control of humanoid robot arms :
       |brobust and adaptive approaches /|cby Adam Spiers, Said 
       Ghani Khan, Guido Herrmann 
264  1 Cham :|bSpringer International Publishing :|bImprint: 
300    1 online resource (xix, 276 pages) :|billustrations (some 
       color), digital ;|c24 cm 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
347    text file|bPDF|2rda 
505 0  Introduction -- Part I Background on Humanoid Robots and 
       Human Motion -- Humanoid Robots and Control -- Human 
       Motion -- Part II Robot Control: Implementation -- Basic 
       Operational Space Controller -- Sliding-Mode Task 
       Controller Modification -- Implementing "Discomfort" for 
       Smooth Joint Limits -- Sliding-Mode Optimal Controller -- 
       Adaptive Compliance Control -- Part III Human Motion 
       Recording for Task Motion Modelling and Robot Arm Control 
       -- Human Motion Recording and Analysis -- Neural Network 
       Motion Learning by Observation for Task Modelling and 
       Control -- Appendices: Kinematics - Introduction -- 
       Inverse Kinematics for BERUL2 -- Theoretical Summary of 
       Adaptive Compliant Controller 
520    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 
650  0 Robots|xControl 
650  0 Robotics 
650  0 Biological control systems 
650 14 Engineering 
650 24 Robotics and Automation 
650 24 Artificial Intelligence (incl. Robotics) 
650 24 Control 
700 1  Khan, Said Ghani,|eauthor 
700 1  Herrmann, Guido,|eauthor 
710 2  SpringerLink (Online service) 
773 0  |tSpringer eBooks 
856 40 |uhttp://dx.doi.org/10.1007/978-3-319-30160-0