贾会群,魏仲慧,何昕,张磊,何家维,穆治亚.基于改进粒子群算法的路径规划[J].农业机械学报,2018,49(12):371-377.
JIA Huiqun,WEI Zhonghui,HE Xin,ZHANG Lei,HE Jiawei,MU Zhiya.Path Planning Based on Improved Particle Swarm Optimization Algorithm[J].Transactions of the Chinese Society for Agricultural Machinery,2018,49(12):371-377.
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基于改进粒子群算法的路径规划   [下载全文]
Path Planning Based on Improved Particle Swarm Optimization Algorithm   [Download Pdf][in English]
投稿时间:2018-07-06  
DOI:10.6041/j.issn.1000-1298.2018.12.044
中文关键词:  机器人  路径规划  粒子群算法  鸡群算法
基金项目:吉林省科技发展计划项目(20180201013GX)
作者单位
贾会群 中国科学院长春光学精密机械与物理研究所 
魏仲慧 中国科学院长春光学精密机械与物理研究所 
何昕 中国科学院长春光学精密机械与物理研究所 
张磊 中国科学院长春光学精密机械与物理研究所 
何家维 中国科学院长春光学精密机械与物理研究所 
穆治亚 中国科学院长春光学精密机械与物理研究所 
中文摘要:传统粒子群算法存在收敛精度低、搜索停滞等缺点,导致机器人路径规划精度低。为了提高路径规划的精度,对传统的粒子群算法进行改进。首先在算法运行的各阶段对惯性权重因子和加速因子同时使用三角函数的变化方式自适应调整,使算法中的参数在算法运行各阶段的配合达到最佳,提高了算法的搜索能力;其次在算法中引入鸡群算法中的母鸡更新方程和小鸡更新方程对搜索停滞的粒子进行扰动,并在引进的方程中使用全局最优解使扰动后的粒子向全局最优解靠近;最后通过函数优化和路径规划两组对比实验,验证了改进算法在问题优化时具有寻优精度高、鲁棒性好的优点。
JIA Huiqun  WEI Zhonghui  HE Xin  ZHANG Lei  HE Jiawei  MU Zhiya
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences,Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences,Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences,Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences,Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences and Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences
Key Words:robot  path planning  particle swarm optimization algorithm  chicken swarm algorithm
Abstract:The traditional particle swarm optimization (PSO) algorithm has some shortcomings such as low convergence precision, stagnant search and so on, which lead to the low precision of robot path planning. In order to improve the precision of path planning, the traditional particle swarm optimization algorithm was improved. Firstly, the inertia weight factor and acceleration factor were adjusted adaptively by the trigonometric function in each stage of the algorithm operation, so that the parameters in the algorithm were optimized in each stage of the algorithm operation, and the search ability of the algorithm was improved. Secondly, the hen equation and chick equation of chicken swarm algorithm were introduced to perturb the search stagnation particles, and the global optimal solution was used in the introduced equation to make the disturbed particle approach the global optimal solution. Finally, through two sets of comparative experiments of function optimization and path planning, it was proved that the improved algorithm had the advantages of high searching precision and good robustness.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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