Evolutionary Membership Adaptation for Mobile Robot Fuzzy Intelligent Behaviors

S. Zein-Sabatto, A. Sekmen, P. Koseeyaporn, and S. Colombano (USA)


Mobile robotics, behaviors, navigation, fuzzy-logic, genetic algorithsm.


A behavior-based mobile robot fuzzy-controller with genetic algorithms for automatic adaptation of robot movements is described. The robot's fuzzy-controller consists of several basic behaviors, i.e., follow-wall, follow-center, move-to-point and avoidance-obstacles combined together to create more complex robot behaviors. The developed fuzzy-genetic behaviors were tested on several robotics tasks such moving the robot to target positions without collision or trapping itself in partially known environments. Simulation and real-time testing results demonstrated significant performance improvements of the robot behaviors by the addition of genetic algorithms to the fuzzy-controller.

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