Analysis on Handling Path Optimization of Agricultural Robots Based on Improved Ant Colony Algorithm

Abstract

With the rapid development of agricultural machinery intelligence and informatization, agricultural robots are becoming the protagonist, promoting standardized production in agriculture, improving efficiency, and reducing labor costs. However, how to quickly plan an efficient and safe path for agricultural transport robots is currently a hot topic in path planning research. In this study, the path optimization problem of agricultural robots handling agricultural products (such as Edible Fungi) in and out of warehouses, which served as the study object, was solved. First, the number of agricultural handling robots was initialized based on the scanning method, and the geometric center of sub-path nodes was set as the virtual node. Secondly, the optimal path of the virtual node was solved using the improved ant colony algorithm embedded with a genetic operator, and the optimal result of sub-paths was acquired. Thirdly, the optimal solution meeting constraint conditions was obtained with the launch cost, transportation cost, and time cost of agricultural robots as objective functions. Lastly, the effectiveness of the optimization model and the improved ant colony algorithm was verified through the instance analysis. This study is of certain significance to the exwarehousing path optimization of agricultural robots under the sustainable development concept of agricultural automation.