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Sensor-based 2-D Potential Panel Method for Robot Motion Planning*

Published online by Cambridge University Press:  09 March 2009

Yanjun Zhang  and
Kimon P. Valavanis
Yanjun Zhang
Affiliation:
A-CIM Center & CACS, The University of Southwestern Louisiana, Lafayette, LA 70504 (USA)
Kimon P. Valavanis
Affiliation:
A-CIM Center & CACS, The University of Southwestern Louisiana, Lafayette, LA 70504 (USA)
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Summary

A potential panel method is proposed to solve simultaneously the path planning and collision avoidance problem for a mobile robot operating in an uncertain obstacle filled environment. The problem is solved in three steps: (1) transform the arbitrary shaped obstacles in the 2-D workspace into simple convex polygons; (2) generate a local minima-free potential field on the workspace; (3) generate a streamline from the starting position towards the goal position in the artificial potential field. The computational complexity of the pertinent algorithms justify the applicability of the approach in real-time. Simulation results are included.

Keywords

Sensor-based motion planningCollision avoidancePotential panel methodPotential field
Type
Articles
Information
Robotica , Volume 14 , Issue 1 , January 1996 , pp. 81 - 89
Copyright
Copyright © Cambridge University Press 1996

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References

1.Zhang, Yanjun, “Sensor-based Potential Panel Method for Robot Motion Planning” PhD thesis (CACS, The University of Southwestern Louisiana, 1995).Google Scholar
2.Khatib, Oussama, “Real-time Obstacle Avoidance for Manipulators and Mobile Robots” Int. J. Robotics Research, 5(1)90–98(1986).CrossRefGoogle Scholar
3.Krogh, B. H., “A Generalised Potential Field Approach to Obstacle Avoidance Control”. In Robotics Research: the next five vears and beyond, SME Conference Proceedings(August. 1984).Google Scholar
4.Riman, Elan and Koditschek, Daniel E., “Exact Robot Navigation using Cost Functions: The Case of Distinct Spherical Boundaries” Proceedings of the IEEE International Conference on Robotics and Automation,Philadelphia. PA(1988) pp. 1791–1796.Google Scholar
5.Riman, Elan and Koditschek, Daniel E., “The Construction of Analytic Diffeomorphisms for Exact Robot Navigation on Star Worlds” Proceedings of the IEEE International Conference on Robotics and automation,Scottsdale, AZ(1989) pp. 21–26.Google Scholar
6.Khosla, Pradeep and Volpe, Richard, “Superquadric Artificial Potentials for Obstacle Avoidance and Approach” Proceedings of the IEEE International Conference on Robotics and Automation,Philadelphia, PA(1988) pp. 648–649.Google Scholar
7.Volpe, Richard and Khosla, Pradeep, “Manipulator Control With Superquadric Artificial Potential Functions: Theory and Experiments.” IEEE Transactions on Svstem and Man and Cybernetics 20(6) 1423–1436 (1990).CrossRefGoogle Scholar
8.Barraquand, Jerome and Latombe, Jean-Claude, “Robot Motion Planning: A Distributed Representation Approach” Int. J. Robotics Research 10(6) 628–649 (1991).CrossRefGoogle Scholar
9.Latombe, Jean-Claude, Robot Motion Planning (Kluwer Academic Publishers, Norwell, MA, 1991).CrossRefGoogle Scholar
10.Megherbi, Dalila and Wolovich, W. A., “Real-Time Velocity Feedback Obstacle Avoidance Via Complex Variables and Conformal Mapping” Proceedings of the IEEE International Conference on Robotics and Automation,Nice, France(1992) pp. 206–213.Google Scholar
11.Kim, Jin-Oh and Khosla, Pradeep K., “Real-Time Obstacle Avoidance Using Harmonic Potential Functions” IEEE Transactions on Robotics and Automation 8(3) 338–349 (1992).CrossRefGoogle Scholar
12.Moran, Jack, An Introduction to Theoretical and Computational Aerodynamics (John Wiley and Sons, Inc., New York, NY, 1984).Google Scholar
13.Tilove, Robert B., “Local Obstacle Avoidance for Mobile Robots Based on the Method of Artificial Potentials” Proceedings of the IEEE International Conference on Robotics and Automation,Cincinnati, OH(1990) pp. 566–571.Google Scholar