A fuzzy logic solution for navigation of an autonomous subsurface planetary exploration robot

An unsupervised fuzzy logic navigation algorithm is designed and simulated for a subsurface planetary exploration robot. The robot is intended for the subsurface exploration of Mars, and will be equipped with acoustic sensing for detecting obstacles. Measurements of obstacle distance and direction are anticipated to be imprecise however, because the performance of acoustic sensors is degraded in underground environments. We present an unsupervised fuzzy logic algorithm that can determine a trajectory for a subsurface planetary exploration robot through unknown environments, even in the presence of imprecise sensor data. This algorithm uses a combination of simple fusion of robot behaviors and self-tuning membership functions to determine robot navigation without resorting to the degree of complexity of previous fuzzy logic algorithms.

[1]  M. Sugeno,et al.  Fuzzy Control of Model Car , 1985 .

[2]  Hoi-Shan Lin,et al.  Evolutionary algorithm for path planning in mobile robot environment , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[3]  Dean Pomerleau,et al.  Efficient Training of Artificial Neural Networks for Autonomous Navigation , 1991, Neural Computation.

[4]  Wei Li,et al.  'Perception-action' behavior control of a mobile robot in uncertain environments using fuzzy logic , 1994, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94).

[5]  Prabir K. Pal,et al.  Mobile robot navigation using a neural net , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[6]  Ho Yim,et al.  Motion planning using fuzzy logic control with minimum sensors , 1995, Proceedings of Tenth International Symposium on Intelligent Control.

[7]  Tomoyoshi Takeuchi,et al.  Fuzzy control of a mobile robot for obstacle avoidance , 1988, Inf. Sci..

[8]  G. S. Vukovich,et al.  Fuzzy evolutionary algorithms and automatic robot trajectory generation , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[9]  Veronica A. Gauss.  A fuzzy logic solution for navigation of the Subsurface Explorer planetary exploration robot , 1997 .

[10]  Sng Hong Lian.  Fuzzy logic control of an obstacle avoidance robot , 1996, Proceedings of IEEE 5th International Fuzzy Systems.

[11]  Simon Handley,et al.  The genetic planner: The automatic generation of plans for a mobile robot via genetic programming , 1993, Proceedings of 8th IEEE International Symposium on Intelligent Control.

[12]  Hyung Suck Cho,et al.  A sensor-based navigation for a mobile robot using fuzzy logic and reinforcement learning , 1995, IEEE Trans. Syst. Man Cybern..

[13]  J. Yung-Jen Hsu,et al.  Fuzzy control for behavior-based mobile robots , 1994, NAFIPS/IFIS/NASA '94. Proceedings of the First International Joint Conference of The North American Fuzzy Information Processing Society Biannual Conference. The Industrial Fuzzy Control and Intellige.

[14]  M. Sugeno,et al.  Fuzzy algorithmic control of a model car by oral instructions , 1989 .