Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-27T11:56:19.707Z Has data issue: false hasContentIssue false

A mobile robot navigation method using a fuzzy logic approach

Published online by Cambridge University Press:  09 March 2009

Bertrand Beaufrere
Affiliation:
Laboratoire de Mécanique des Solides (U.R.A. 861), Université de Poitiers, 40, Avenue du Recteur Pineau, 86022 Poitiers Cedex (France)
Saïd Zeghloul
Affiliation:
Laboratoire de Mécanique des Solides (U.R.A. 861), Université de Poitiers, 40, Avenue du Recteur Pineau, 86022 Poitiers Cedex (France)

Summary

This paper treats, in a general way, the problem of mobile robot navigation in a totally unknown environment. The different aspects of this problem are dealt with one by one. We begin by introducing a simple method for perceiving and analyzing the robot's local environment based on a limited amount of distance information. Using this analysis as our base, we present a navigation algorithm containing different action modules; some of these actions use Fuzzy Logic. The results presented whether experimental or simulation show that our method is well adapted to this type of problem.

Type
Articles
Copyright
Copyright © Cambridge University Press 1995

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Takeuchi, T., Nagai, Y. and Enomoto, Y., “Fuzzy Control of a Mobile Robot for Obstacle Avoidance”, Information Sciences, 45(2), 231248 (1988).CrossRefGoogle Scholar
2.Yagi, Y., Nishimitsu, Y. and Yachida, M., “Map based Navigation of the Mobile Robot using Omnidirectional Image Sensor COPIS” Proceedings of IEEE Conference on Robotics and Automation,Nice, France, (1992) pp. 4752.Google Scholar
3.Crowley, J.L. and Coutaz, J., “Navigation et modélisation pour un robot mobileTechnique et Science Informatiques 5(5), 391402 (1986).Google Scholar
4.Borenstein, J. and Koren, Y., “Noise Rejection for Ulltrasonic Sensors in Mobile Robot Application” Proceedings of IEEE Conference on Robotics and Automation,Nice, France (1992) pp. 17271732.Google Scholar
5.Buchberger, M., Jörg, K. and Puttkamer, E.v., “Laserradar and Sonar Based World Modeling and Motion Control for Fast Obstacle Avoidance of the Autonomous Mobile Robot MOBOT-IV” Proceedings of IEEE Conference on Robotics and Automation,Atlanta, Georgia (1993) pp. 534540.Google Scholar
6.Cho, D.W., “Certainty Grid Representation for Robot Navigation by a Bayesian MethodRobotica 8, 1159–165 (1990).CrossRefGoogle Scholar
7.Borenstein, J. and Koren, Y., “The Vector Field Histogram - Fast Obstacle Avoidance for Mobile RobotsIEEE Transactions on Robotics and Automation 7, No. 3, 278288 (1991).CrossRefGoogle Scholar
8.Lozano-Perez, T. and Wesley, M.A., “An Algorithm for Planning Collision Free Paths Among Polyhedral Obstacles” ACM22, No. 10, 560570 (1979).Google Scholar
9.Khatib, O., “Real-Time Obstacle Avoidance for Manipulators and Mobile Robot” Proceedings of IEEE Conference on Robotics and Automation (1985), pp. 500505.Google Scholar
10.Warren, C.W., “Multiple Robot Path Coordination Using Artificial Potential Fields” Proceedings of IEEE Conference on Robotics and Automation,Cincinnati, Ohio (1990). pp. 500505.Google Scholar
11.POLAROID Corporation, Ultrasonic Components Group (Cambridge, MA, 1990).Google Scholar
12.Beaufrere, B. and Zeghloul, S., “Trajectory Planning for a Mobile Robot in an Unknown Environment by Fuzzy Based Method” ASME International Computers in Engineerings San Diego, California (1993) pp 171174.Google Scholar
13.Zadeh, L.A., “Fuzzy sets”, Information and Control No. 8, 338353 (1965).Google Scholar
14.Takagi, T. and Sugeno, M., “Fuzzy identification of systems and its applications to modeling and controlIEEE Trans. on Systems, Man and Cybernetics SMC15, No. 1, 116132 (1985).CrossRefGoogle Scholar