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Wireless Personal Communications

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13-02-2018

Off-road Path Planning Based on Improved Ant Colony Algorithm

Authors: Han Wang, Hongjun Zhang, Kun Wang, Chen Zhang, Chengxiang Yin, Xingdang Kang

Published in: Wireless Personal Communications | Issue 2/2018

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Abstract

Optimal vehicle off-road path planning problem must consider surface physical properties of terrain and soil. In this paper, we firstly analyse the comprehensive influence of terrain slope and soil strength to vehicle’s off-road trafficability. Given off-road area, the GO or NO-GO tabu table of terrain gird is determined by slope angle and soil remolding cone index (RCI). By applying tabu table and grid weight table, the influence of terrain slope and soil RCI are coordinated to reduce the search scope of algorithm and improve search efficiency. Simulation results based on tracked vehicle M1A1 in off-road environment show that, improved ant colony path planning algorithm not only considers the influence of actual terrain and soil, but also improves computation efficiency. The time cost of optimal routing computation is much lower which is essential for real time off-road path planning scenarios.

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Title: Off-road Path Planning Based on Improved Ant Colony Algorithm
Authors: Han Wang
Hongjun Zhang
Kun Wang
Chen Zhang
Chengxiang Yin
Xingdang Kang
Publication date: 13-02-2018
Publisher: Springer US
Published in: Wireless Personal Communications / Issue 2/2018
Print ISSN: 0929-6212
Electronic ISSN: 1572-834X
DOI: https://doi.org/10.1007/s11277-017-5229-5

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