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Coordinated Path Following Control of Multiple Vehicles subject to Bidirectional Communication Constraints

  • R. Ghabcheloo
  • A. Pascoal
  • C. Silvestre
  • I. Kaminer
Chapter
Part of the Lecture Notes in Control and Information Science book series (LNCIS, volume 336)

Abstract

The paper addresses the problem of making a set of vehicles follow a a set of given spatial paths at required speeds, while ensuring that they reach and maintain a desired formation pattern. Problems of this kind arise in a number of practical applications involving ground and underwater robots. The paper summarizes and brings together in a unified framework previous results obtained by the authors for wheeled robots and fully actuated underwater vehicles. The decentralized solution proposed does not require the concept of a leader and applies to a very general class of paths. Furthermore, it addresses explicitly the dynamics of the vehicles and the constraints imposed by the inter-vehicle bi-directional communications network. The theoretical machinery used brings together Lyapunov-based techniques and graph theory. With the set-up proposed, path following (in space) and inter-vehicle coordination (in time) can be viewed as essentially decoupled. Path following for each vehicle is formulated in terms of driving a conveniently defined generalized error vector to zero; vehicle coordination is achieved by adjusting the speed of each vehicle along its particular path, based on information on the position and speed of a number of neighboring vehicles, as determined by the communications topology adopted. The paper presents the problem formulation and summarizes its solution. Simulations with dynamics models of a wheeled robot and an underwater vehicle illustrate the efficacy of the solution proposed.

Keywords

Underwater Vehicle Autonomous Underwater Vehicle Network Control System Communication Topology Communication Constraint 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin/Heidelberg 2006

Authors and Affiliations

  • R. Ghabcheloo
    • 1
  • A. Pascoal
    • 1
  • C. Silvestre
    • 1
  • I. Kaminer
    • 2
  1. 1.Institute for Systems and Robotics/Instituto Superior Técnico (IST), Av. Rovisco Pais 1, 1049-001 LisboaPortugal
  2. 2.Department of Mechanical and Astronautical Engineering, Naval Postgraduate School, Monterey, CA 93943USA

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