Title :
Fuzzy neural network based dynamic path planning
Author :
Jiang, Min ; Yu, Yang ; Liu, Xiaoli ; Zhang, Fan ; Hong, Qingyang
Author_Institution :
Dept. of Cognitive Sci., Xiamen Univ., Xiamen, China
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 :
collision avoidance; fuzzy neural nets; mobile robots; collision prediction; dynamic path planning; fuzzy membership function; fuzzy neural network; mobile robot; obstacle avoidance; Abstracts; Fuzzy neural networks; Planning; Propulsion; Robots; Yttrium; Dynamic Path Planning; Fuzzy-Neural Networks; Membership Function;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2012 International Conference on
Conference_Location :
Xian
Print_ISBN :
978-1-4673-1484-8
DOI :
10.1109/ICMLC.2012.6358934