Dynamic grasping system based on visual algorithm and robot arm collaboration in logistics production line - Bowen He; Bin Chen (PLoS ONE, 2026)
In response to the urgent need for efficient and accurate dynamic grasping in automated logistics, this study proposes the VRCDS, a dynamic grasping system that integrates a multi-feature weighted PnP vision algorithm with multi-robot arm collaboration. The system establishes a closed-loop “perception-decision-execution-feedback” architecture, significantly enhancing grasping accuracy, system efficiency, and energy savings compared to traditional single-arm or visual servo schemes. Experimental results demonstrate that the VRCDS system achieves high recognition accuracy, robust grasping efficiency under various conveyor speeds, precise trajectory control, and a substantial reduction in power consumption. The research provides an efficient, precise, and reliable solution for dynamic grasping tasks in logistics automation.