An efficient data-driven fuzzy approach to the motion planning problem of a mobile robot

  • Authors:

  • Mohannad Al-Khatib;Jean J. Saade

  • Affiliations:

  • ECE Department, FEA, American University of Beirut, P.O.Box: 11-0236, Riad El-Solh, Beirut 1107 2020, Lebanon;ECE Department, FEA, American University of Beirut, P.O.Box: 11-0236, Riad El-Solh, Beirut 1107 2020, Lebanon

  • Venue:
  • Fuzzy Sets and Systems - Special issue: Fuzzy set techniques for intelligent robotic systems
  • Year:
  • 2003

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Abstract

A data-driven fuzzy approach is developed for solving the motion planning problem of a mobile robot in the presence of moving obstacles. The approach consists of devising a general method for the derivation of input-output data to construct a fuzzy logic controller (FLC) off-line. The FLC is constructed based on the use of a recently developed data-driven and efficient fuzzy controller modeling algorithm, and it can then be used on-line by the robot to navigate among moving obstacles. The novelty in the presented approach, as compared to the most recent fuzzy ones, stems from its generality. That is, the devised data-derivation method enables the construction of a single FLC to accommodate a wide range of scenarios. Also, care has been taken to find optimal or near optimal FLC solution in the sense of leading to a sufficiently small robot travel time and collision-free path between the start and target points. Furthermore, since the algorithm has been shown efficient in the representation of non-linear control functions, in terms of combating noise and possessing a good generalization capability, these aspects are also tested in this practical control problem. Comparison of the results with those obtained by fuzzy-genetic and another hybrid and data-driven design approach is also done.