Abstract

This paper proposes a novel Redundant Cooperative Control (RCC) strategy to address the pollination sequence planning problem for a mobile pollination robot in the greenhouse. Firstly, the RCC strategy divides the robot’s workspace into subspaces based on the distribution of flowers through clustering. Subsequently, the RCC strategy plans the traveling salesman problem within the visual field of these subspaces, seeking a compromise solution for an optimal path. Finally, the RCC strategy utilizes the redundant motion capabilities of the mobile chassis and robotic arm to accomplish the pollination task during the movement. The RCC strategy exploits the available redundancy in both the agricultural robot’s mobile platform and end-effector, carefully balancing computational complexity and path quality. To validate the effectiveness of the RCC strategy, we designed a series of experiments conducted on our pollination robot platform, measuring different strategies. The results demonstrate that the RCC strategy achieves an average pollination rate of 7.5 s per flower, representing a 36.4% improvement compared to the most common intermittence strategy. Furthermore, the RCC strategy can be extended to tasks such as harvesting and pruning, significantly enhancing the efficiency of robot task execution even in industrial and service sectors.

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