A fuzzy algorithm for navigation of mobile robots in unknown environments

A fuzzy algorithm is proposed to navigate a mobile robot in a completely unknown environment. The mobile robot is equipped with an electronic compass and two optical encoders for dead-reckoning, and two ultrasonic modules for self-localization and environment recognition. From the readings of sensors at every sampling instant, the proposed fuzzy algorithm determines the priorities of thirteen possible heading directions. Then, the robot is driven to an intermediate configuration along the heading direction that has the highest priority. The navigation procedure is iterated until the final configuration is reached. To show the feasibility of the proposed method, experimental results are given.

[1]  Narendra Ahuja,et al.  Path planning using a potential field representation , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.

[2]  Lydia E. Kavraki,et al.  Analysis of probabilistic roadmaps for path planning , 1998, IEEE Trans. Robotics Autom..

[3]  Wei Li,et al.  A neuro-fuzzy system architecture for behavior-based control of a mobile robot in unknown environments , 1997, Fuzzy Sets Syst..

[4]  Kimon P. Valavanis,et al.  Autonomous vehicle navigation utilizing electrostatic potential fields and fuzzy logic , 2001, IEEE Trans. Robotics Autom..

[5]  Chia-Ju Wu,et al.  Localization of an Autonomous Mobile Robot Based on Ultrasonic Sensory Information , 2001, J. Intell. Robotic Syst..

[6]  D. Lane,et al.  Subsea vehicle path planning using nonlinear programming and constructive solid geometry , 1997 .

[7]  Chin-Teng Lin,et al.  Neural fuzzy systems , 1994 .

[8]  Sauro Longhi,et al.  Motion planning for unicycle and car-like robots , 1996, Int. J. Syst. Sci..

[9]  Elmer G. Gilbert,et al.  Distance functions and their application to robot path planning in the presence of obstacles , 1985, IEEE J. Robotics Autom..

[10]  Eric T. Baumgartner,et al.  An autonomous vision-based mobile robot , 1994, IEEE Trans. Autom. Control..

[11]  Sadayuki Tsugawa,et al.  Vision-based vehicles in Japan: machine vision systems and driving control systems , 1994, IEEE Trans. Ind. Electron..

[12]  Ching-Chih Tsai.  A localization system of a mobile robot by fusing dead-reckoning and ultrasonic measurements , 1998, IMTC/98 Conference Proceedings. IEEE Instrumentation and Measurement Technology Conference. Where Instrumentation is Going (Cat. No.98CH36222).

[13]  Vijay Kumar,et al.  A potential field based approach to multi-robot manipulation , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[14]  Petros A. Ioannou,et al.  New Potential Functions for Mobile Robot Path Planning , 2000 .

[15]  Daniel E. Koditschek,et al.  Exact robot navigation using artificial potential functions , 1992, IEEE Trans. Robotics Autom..

[16]  Liqiang Feng,et al.  Measurement and correction of systematic odometry errors in mobile robots , 1996, IEEE Trans. Robotics Autom..

[17]  Lydia E. Kavraki,et al.  Analysis of probabilistic roadmaps for path planning , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[18]  Hong Xu,et al.  LiAS: a reflexive navigation architecture for an intelligent mobile robot system , 1996, IEEE Trans. Ind. Electron..

[19]  Chia-Ju Wu.  A learning fuzzy algorithm for motion planning of mobile robots , 1994, J. Intell. Robotic Syst..