Abstract: In recent years, multi-arm tea-picking robots have become a research hotspot due to the shortage of labor, rising labor costs, and the demand for high-precision picking in the high-quality tea industry. A collaborative planning method that dynamically allocates the space for picking points was proposed, and the path planning of the robotic arm was optimized by combining the ant colony algorithm and the picking point priority in order to improve the operational efficiency of the tea-picking robot. Simulation results show that the average time for one-shoot picking was 1.41 s, and the time ratio for dual-arm synchronous operation was 91.95%. Compared to the 62.86% coverage rate of the two-space segmentation method, this method achieved full coverage of the space. To overcome the limitations of the existing independent operation mode of the depth camera, a dynamic addition of picking point planning was further proposed, which realized the synchronous operation of the depth camera and the robotic arm. Field experiment results show that the tea-picking robot adopts the picking point allocation method that dynamically divides the operating space and the double-arm collaborative planning method that dynamically divides the space for picking point allocation. The average time for one-shoot picking was 1.52 s, a 29.95% improvement compared to the one-arm tea-picking robot. This method not only significantly improves the operational efficiency of the tea-picking robot but also achieves full coverage of the space, ensuring efficient collaborative picking.

Key words: picking robot, multi-arm, collaborative picking planning, dynamic picking point addition planning