A Fuzzy Adaptive Rapid-Exploring Random Tree Algorithm

Meng Li, Qing Song, Qinjun Zhao


In view of the deficiency of the traditional RRT algorithm parameters setting, a fuzzy adaptive RRT algorithm is proposed based on the analysis of RRT realization mechanism. According to the number of random nodes and the total nodes in tree, a fuzzy inference system is designed, which can adaptive update selection probability g p and step length  . Chaotic sequence is adopted to generate initial random node position. The simulation results show that new strategy can set parameters more reasonable; improve the efficiency and the success rate obvious, especially for complex task environment.


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