rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Biologically Inspired Control of Humanoid Robot Arms
    sub title: Robust and Adaptive Approaches
  name:
    name part: Spiers, Adam.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Khan, Said Ghani.
    role:
      role term: author.
  name:
    name part: Herrmann, Guido.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2016
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIX, 276 p. 145 illus., 128 illus. in color. online resource.
  abstract: 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-…
  table of contents: 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.
  note: by Adam Spiers, Said Ghani Khan, Guido Herrmann.
  subject:
    topic: Engineering
  subject:
    topic: Artificial intelligence
  subject:
    topic: Control engineering
  subject:
    topic: Robotics
  subject:
    topic: Automation
  subject:
    topic: Engineering
  subject:
    topic: Robotics and Automation
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Control
  classification: TJ210.2-211.495
  classification: T59.5
  classification: 629.892
  related item:
    title info:
      title: Springer eBooks
  identifier: 9783319301600
  identifier: http://dx.doi.org/10.1007/978-3-319-30160-0
  record info:
    record creation date: 160519
    record change date: 20160525131405.0
    record identifier: 978-3-319-30160-0