A rapid path planning adaptive optimization algorithm based on fuzzy neural network for multi-robot systems

A rapid path planning adaptive optimization algorithm based on fuzzy neural network is proposed for mobile robot in a static unknown environment. In order to solve the limitations of the subjective experience in the fuzzy control and design problems of path planning, conventional neural network is given fuzzy input signals and fuzzy weights by using the membership function and the error cost function of fuzzy control theory. Neural network is constructed from fuzzy rules to accelerate the convergence of FNN, so that the collision-free motion is achieved by combining with the formation control method for mobile robot. Finally, the experiment results show that the robot path planning based on FNN algorithm is faster than other algorithms to finish the task as well as a better controllability and adaptability by the platform of Player/Stage.