UAV 3D path planning based on improved ant colony algorithm

Sheng Ding; Zhihong Liang; Bo Liu

doi:10.1117/12.2675274

25 May 2023 UAV 3D path planning based on improved ant colony algorithm

Sheng Ding, Zhihong Liang, Bo Liu

Proceedings Volume 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022); 126364X (2023) https://doi.org/10.1117/12.2675274
Event: Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 2022, Shenyang, China

Abstract

Aiming at the problems that traditional ant colony algorithm is prone to fall into the local optimal solution and the convergence speed is slow in 3D path planning of UAVS, an improved ant colony algorithm is proposed for 3D path planning of UAVS. By improving the pheromone evaporation coefficient and combining with the evaluation function of A* algorithm, a three-dimensional environment model is constructed by using the grid method, and then experimental simulation is carried out. The results show that the convergence speed of the improved ant colony algorithm is faster and the optimal path is shorter than the traditional one.

Citation Download Citation

Sheng Ding, Zhihong Liang, and Bo Liu "UAV 3D path planning based on improved ant colony algorithm", Proc. SPIE 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 126364X (25 May 2023); https://doi.org/10.1117/12.2675274

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