农机化研究2024，Vol.46Issue(4)：188-192,5.
基于多因子量化选股模型的采摘机器人学习策略研究
Study on Learning Strategy of Picking Robot Based on Multi Factor Quantitative Stock Selection Model
摘要
Abstract
It first analyzes the multi factor quantitative stock selection model,builds the model of the picking robot′s learning strategy,then improves the ant colony algorithm by using the multi factor quantitative stock selection model,and analyzes and studies the path planning of the picking robot by using the improved ant colony algorithm.The results of Matlab experiments show that the algorithm has planned an optimal path with the shortest length and the least number of turns for the picking robot,and there is no collision during the moving process,which proves that the algorithm has obvi-ous effect on improving the moving path of the picking robot and makes the planned path more reasonable.关键词
采摘机器人/学习策略/路径规划/蚁群算法/多因子量化Key words
picking robot/learning strategies/path planning/ant colony/multifactor quantification分类
农业科技引用本文复制引用
赵睿..基于多因子量化选股模型的采摘机器人学习策略研究[J].农机化研究,2024,46(4):188-192,5.基金项目
河南省社会科学界联合会调研项目(SKL-2021-2929) （SKL-2021-2929）
