Tea Picking Path Planning Based on Ant Colony Algorithm
Guangjun Wang, Yi Zhao, Zhi Wang, Yangzheng Zhang · 2022 41st Chinese Control Conference (CCC) · 2022
In order to improve the efficiency of tea picking, a scheme combining ant colony algorithm and tea picking technology is proposed to plan the picking path. In this scheme, k-means clustering algorithm is used to divide the tea picking regions with irregular growth. The ant colony algorithm is used to carry out path planning for tea in different picking areas, and the best picking effect is selected according to the simulation results. To solve the problem of long searching time of ant colony algorithm, the condition of iteration termination is changed to adaptive value, and the optimal route after the last iteration is recorded as the initial value of the next iteration. The simulation results show that the best effect is to divide two picking regions. The improved ant colony algorithm reduces the operation time and the planned picking path is shorter, which can enhance the real-time tea picking and improve the efficiency of tea picking.