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: 3D-Position Tracking and Control for All-Terrain Robots
  name:
    name part: Lamon, Pierre.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2008
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XVI, 108 p. 56 illus. online resource.
  abstract: Rough terrain robotics is a fast evolving field of research and a lot of effort is deployed towards enabling a greater level of autonomy for outdoor vehicles. This book demonstrates how the accuracy of 3D position tracking can be improved by considering rover locomotion in rough terrain as a holistic problem. Although the selection of appropriate sensors is crucial to accurately track the rover’s position, it is not the only aspect to consider. Indeed, the use of an unadapted locomotion concept severely affects the signal to noise ratio of the sensors, which leads to poor motion estimates. In this work, a mechanical structure allowing smooth motion across obstacles with limited wheel slip is used. In particular, it enables the use of odometry and inertial sensors to improve the position estimation in rough terrain. A method for computing 3D motion increments based on the wheel encoders and chassis state sensors is developed. Because it accounts for the kinematics of the rover, this method provides better results than the standard approach. To further improve the accuracy of the position tracking and the rover’s climbing performance, a controller minimizing wheel slip is developed. The algorithm runs online and can be adapted to any kind of passive wheeled rover. Finally, sensor fusion using 3D-Odometry, inertial sensors and visual motion estimation based on stereovision is presented. The experimental results demonstrate how each sensor contributes to increase the accuracy and robustness of the 3D position estimation.
  table of contents: The SOLERO Rover -- 3D-Odometry -- Control in Rough-Terrain -- Position Tracking in Rough-Terrain -- Conclusion -- Kinematic and Quasi-static Model of SOLERO -- Linearized Models -- The Gauss–Markov Process -- Visual Motion Estimation.
  note: by Pierre Lamon.
  subject:
    topic: Engineering
  subject:
    topic: Artificial intelligence
  subject:
    topic: System theory
  subject:
    topic: Control engineering
  subject:
    topic: Robotics
  subject:
    topic: Mechatronics
  subject:
    topic: Automation
  subject:
    topic: Engineering
  subject:
    topic: Robotics and Automation
  subject:
    topic: Control, Robotics, Mechatronics
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Systems Theory, Control
  classification: TJ210.2-211.495
  classification: T59.5
  classification: 629.892
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Springer Tracts in Advanced Robotics, 43
  identifier: 9783540782872
  identifier: http://dx.doi.org/10.1007/978-3-540-78287-2
  record info:
    record creation date: 100301
    record change date: 20151204185530.0
    record identifier: 978-3-540-78287-2