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A layered goal-oriented fuzzy motion planning strategy for mobile robot navigation.

Xiaoyu Yang1, Mehrdad Moallem, Rajni V Patel

  • 1Department of Electrical and Computer Engineering, University of Western Ontario, Canada. xyang23@engga.uwo.ca

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|December 22, 2005
PubMed
Summary

This study introduces a fuzzy logic-based motion planning strategy for mobile robots navigating unknown environments. The system effectively guides robots to goals using a layered approach, ensuring collision avoidance and real-time performance.

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Control Systems

Background:

  • Conventional motion planning algorithms struggle with dynamic, unknown environments.
  • Real-world mobile robot navigation requires adaptable strategies.
  • Model-based approaches are insufficient for unpredictable settings.

Purpose of the Study:

  • To develop a layered, goal-oriented motion planning strategy for mobile robots in unknown environments.
  • To utilize fuzzy logic for robust and efficient navigation.
  • To enable real-time path planning and collision avoidance.

Main Methods:

  • A two-layer fuzzy logic-based motion planner was designed.
  • The first layer uses global goals and long-range data to set way-points.

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  • The second layer uses short-range data to reach way-points while avoiding obstacles.

    • Main Results:

    • The proposed strategy generates paths similar to visibility graphs without environment assumptions.
    • Fuzzy logic enables simplicity and real-time implementation.
    • Experimental results on the Koala robot demonstrate system effectiveness.

    Conclusions:

    • The fuzzy logic-based navigation system is effective for mobile robots in unknown environments.
    • The layered approach successfully integrates global and local navigation.
    • The system offers a practical solution for real-world robot navigation challenges.