Wireless Personal Communications

, Volume 102, Issue 2, pp 1705–1721 | Cite as

Off-road Path Planning Based on Improved Ant Colony Algorithm

  • Han WangEmail author
  • Hongjun Zhang
  • Kun Wang
  • Chen Zhang
  • Chengxiang Yin
  • Xingdang Kang


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.


Off-road mobility Path planning Ant colony Terrain slope Remolding cone index 



The authors acknowledge the National Natural Science Foundation of China (Grant No: 61273047), the National Natural Science Foundation of China (Grant No: 61573376).


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Han Wang
    • 1
    • 2
    Email author
  • Hongjun Zhang
    • 1
  • Kun Wang
    • 1
  • Chen Zhang
    • 1
  • Chengxiang Yin
    • 1
  • Xingdang Kang
    • 1
  1. 1.Army Engineering UniversityNanjingChina
  2. 2.NanjingChina

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