Toward efficient trajectory planning: the path-velocity decomposition
International Journal of Robotics Research
Robot Motion Planning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Multi-agent systems by incremental gradient reinforcement learning
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
A genetic-fuzzy approach for mobile robot navigation among moving obstacles
International Journal of Approximate Reasoning
Multiobjective quantum-inspired evolutionary algorithm for fuzzy path planning of mobile robot
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Evolutionary multi-objective optimization in robot soccer system for education
IEEE Computational Intelligence Magazine
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We consider the difficult path planning problem for a team of robots working in the same workspace. Their navigation movements are determined by the fuzzy logic controllers (FLCs) having a common knowledge base which consists of membership function distributions and fuzzy rules. Such an FLC requires the design of an appropriate knowledge base. We propose, in this paper, to automate this design task by use of a genetic algorithm (GA) which selects some good rules from a large rule base using the information of membership function distributions of the variables. Results of computer simulations are given which demonstrate the feasibility of this approach.