Trajectory planning for distributed multi-UAVs based on improved DWA

In response to the autonomous obstacle avoidance problem of multiple unmanned aerial vehicles under the influence of static and dynamic obstacles in complex operating environments, an optimized dynamic window method based on avoidance responsibility is proposed. Firstly, based on different types of conflicts, a new principle for dividing the collision zone of unmanned aerial vehicles is proposed, which refines the relief strategies and means adopted when encountering different conflicts. Secondly, based on the principle of conflict resolution and obstacle avoidance, a new responsibility evaluation function was designed to restrict and constrain specific drone conflict resolution actions. Finally, based on Matrix Laboratory (MATLAB) simulation verification, the improved optimization algorithm can effectively improve efficiency of trajectory planning and the success rate, especially when dealing with left and right-side conflicts. The planned path length was shortened by 6.6% and 26% respectively, and the planning time was reduced by 5.8% and 10% respectively, further verifying the superiority of the improved algorithm and effectively avoiding the local optimal path problem caused by unreasonable avoidance.

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Publication Details

Published
2025-04-25
DOI
https://doi.org/10.1117/12.3061920
Citations
1
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
1.28

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article

Trajectory planning for distributed multi-UAVs based on improved DWA

S. Wang, dechao wang, Qing Cheng, Yi Ai
1 citations
Robotic Path Planning Algorithms
1.28
article

Trajectory planning for distributed multi-UAVs based on improved DWA

S. Wang, dechao wang, Qing Cheng, Yi Ai
article en
1 citations

Abstract

In response to the autonomous obstacle avoidance problem of multiple unmanned aerial vehicles under the influence of static and dynamic obstacles in complex operating environments, an optimized dynamic window method based on avoidance responsibility is proposed. Firstly, based on different types of conflicts, a new principle for dividing the collision zone of unmanned aerial vehicles is proposed, which refines the relief strategies and means adopted when encountering different conflicts. Secondly, based on the principle of conflict resolution and obstacle avoidance, a new responsibility evaluation function was designed to restrict and constrain specific drone conflict resolution actions. Finally, based on Matrix Laboratory (MATLAB) simulation verification, the improved optimization algorithm can effectively improve efficiency of trajectory planning and the success rate, especially when dealing with left and right-side conflicts. The planned path length was shortened by 6.6% and 26% respectively, and the planning time was reduced by 5.8% and 10% respectively, further verifying the superiority of the improved algorithm and effectively avoiding the local optimal path problem caused by unreasonable avoidance.

Civil Aviation Flight University of China (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 21%
Robotic Path Planning Algorithms
1.28
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