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Fuzzy neural network based dynamic path planning

Min Jiang, Yu Yang, Xiaoli Liu, Fan Zhang, Qingyang Hong

Year
2012
Citations
17

Abstract

It is an important issue for mobile robot to find the best route as well as avoid moving into obstacles. In this article, we put forward a solution to the problem by using fuzzy-neural network. Compared with the other path planning approaches, one of the main advantages of the methods based on fuzzy-neural network is that they give stronger robustness to the robot. Different from the similar methods, we introduce a novel fuzzy membership function which is based on collision prediction. This method not only preserves the advantages of the existing ones, but also can give a realistic meaning to the path gotten from this approach. The simulation results prove the feasibility and validity of our method.

Keywords

Robustness (evolution)Computer scienceArtificial neural networkFuzzy logicMotion planningArtificial intelligenceMobile robotFuzzy control systemNeuro-fuzzyPath (computing)

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