Open AccessResearch and Application of Path Planning Algorithm in Complex Terrain
Author(s) -
Yunxiang Liu,
Weiqiang Xu
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1570/1/012008
Subject(s) - terrain , motion planning , path (computing) , artificial neural network , algorithm , function (biology) , computer science , field (mathematics) , artificial intelligence , geography , mathematics , robot , cartography , evolutionary biology , biology , programming language , pure mathematics
Aiming at the failure of path planning in complex three-dimensional terrain, a path planning algorithm based on Hopfield neural network is proposed. According to the three-dimensional terrain, the undulating terrain and obstacles are transformed into a calculable regular figure, and the terrain function model is established according to the flow field control equation; the terrain function model is effectively integrated with Hopfield neural network algorithm. The algorithm is applied to complex three-dimensional terrain environment, can avoid undulating terrain and obstacles, and find an optimal path, which lays an important foundation for the navigation vehicle path planning.