基于改进麻雀搜索算法的农业机器人路径规划
Path planning for agricultural robots based on improved sparrow search algorithm
毛爽 1代永强 1刘欢1
作者信息
- 1. 甘肃农业大学信息科学技术学院,甘肃 兰州 730070
- 折叠
摘要
针对农业机器人在进行路径规划时存在寻优结果差和搜索稳定性低的问题,提出一种改进的麻雀搜索算法SSAPSO.首先利用Cubic混沌映射初始化种群来增强麻雀种群位置的多样性.然后通过萤火虫扰动策略,增加算法的灵活性和搜索范围.最后引入粒子群技术以提高算法的寻优精度和稳定性.实验结果表明,在不同障碍物覆盖率的栅格地图环境下,SSAPSO能高效且稳定地求解农业机器人最优路径,从而提高农业机器人的工作效率.
Abstract
An improved sparrow search algorithm,SSAPSO,is proposed to address the problems of poor search results and low search stability in path planning for agricultural robots.Firstly,Cubic chaotic mapping is used to initialize the population to enhance the diversity of sparrow population locations.Then,a firefly perturbation strategy is used to increase the flexibility and search range of the algorithm.Finally,particle swarm techniques are introduced to improve the search accuracy and stability.The experimental results show that SSAPSO can solve the optimal path of agricultural robots efficiently and stably in a raster map environment with different obstacle coverage,thus improving the efficiency of agricultural robots.
关键词
麻雀搜索算法/粒子群算法/农业机器人/路径规划Key words
sparrow search algorithm(SSA)/particle swarm optimization(PSO)algorithm/agricultural robot/path planning引用本文复制引用
基金项目
甘肃省高等学校创新基金(2022B-107)
甘肃省高等学校创新基金(2019A-056)
甘肃省自然科学基金(20JR10RA510)
甘肃省自然科学基金(1506RJZA007)
甘肃省自然科学基金资助项目(20JR10RA510)
出版年
2023
NETL
NSTL
维普
万方数据