Raster map path planning based on intelligent optimization algorithms

Meixia Suo; Yongli Zhang; Lili Wang; Xinqi Li

doi:10.1117/12.3004876

9 October 2023 Raster map path planning based on intelligent optimization algorithms

Meixia Suo, Yongli Zhang, Lili Wang, Xinqi Li

Proceedings Volume 12791, Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023); 127910I (2023) https://doi.org/10.1117/12.3004876
Event: Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023), 2023, Qingdao, SD, China

Abstract

To solve the problem of obstacle avoidance cars find the shortest path without collision between two locations. Firstly, the method of building a raster map is used in MATLAB to simulate the working environment of the trolley. Secondly, a hybrid algorithm combining particle swarm algorithm and genetic algorithm is proposed, and it is applied to the path optimization of the trolley. The hybrid algorithm combines the traditional particle swarm algorithm and the genetic algorithm, retains the speed and position iteration mode of the particle swarm algorithm, and integrates the cross and mutation operations in the genetic algorithm. The results show that compared with the traditional particle swarm algorithm and genetic algorithm, the hybrid algorithm can enhance the ability to jump out of local extremes in the process of population search, improve the convergence progress of the algorithm, and ensure that the obstacle avoidance trolley can find a more suitable moving path between the starting point and the target point.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Meixia Suo, Yongli Zhang, Lili Wang, and Xinqi Li "Raster map path planning based on intelligent optimization algorithms", Proc. SPIE 12791, Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023), 127910I (9 October 2023); https://doi.org/10.1117/12.3004876

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