Abstract
Abstract
A modified Hopfield neural network algorithm is proposed and applied to the path planning to solve some problems in the traditional Hopfield neural network. Firstly, the traditional A* algorithm is used to select the nodes in the search area that meet the criteria. Then, the nodes conforming to the standard are converted into neurons in the Hopfield neural network, and the stability of the network is used to iteratively select an optimal path. Experiments show that the improved Hopfield neural network algorithm can reduce the search time of path planning and improve efficiency.
Subject
General Physics and Astronomy
Reference11 articles.
1. Evolutionary algorithm based offline/online path planner for UAV navigation;Nikolos;IEEE Trans Syst Man Cybern Part B: Cybern,2003
2. Optimal flflight path planner for an unmanned helicopter by evolutionary algorithms;Zhao,2007
3. Path-Value Functions for Which Dijkstra’s Algorithm Returns Optimal Mapping;Ciesielski;Journal of Mathematical Imaging and Vision,2018
4. Application of improved artificial potential field method in obstacle avoidance of unmanned vehicles[J];Tan;Journal of Xi’an University of Technology,2014
5. Novel robust approach for constructing Mamdani-type fuzzy system based on PRM and subtractive clustering algorithm;Fei;Journal of Central South University,2015
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