食品协作机器人动态目标抓取控制方法研究

目的:解决目前协作机器人在食品动态目标抓取中存在的准确性较低问题。方法:基于协作机器人体系结构，提出将模糊自整定PID控制和鲁棒自适应补偿器相结合用于协作机器人食品动态目标抓取。PID结合模糊控制完成参数自整定，鲁棒算法与自适应算法相结合用于系统不确定性补偿。通过试验分析了所提方法的性能，验证了该方法的可行性。结果:所提方法在协作机器人动态目标抓取中具有较好的效果，提高了协作机器人动态抓取的准确性，在传送带速度100 mm/s时，动态抓取成功率达到99.50%,对食品动态目标抓取具有一定的应用价值。结论:通过优化现有目标抓取控制方法，可有效提高协作机器人的抓持精度。

Research on dynamic target grasping control method for food collaborative robot

Objective: Solve the problem of low accuracy of collaborative robots in food dynamic target grasping at present. Methods: Based on the architecture of collaborative robots, a combination of fuzzy self-tuning PID control and robust adaptive compensator was proposed for collaborative robot food dynamic target grasping. PID combined with fuzzy control to achieve parameter self-tuning, and robust algorithm combined with adaptive algorithm for system uncertainty compensation. The performance of the proposed method was analyzed through experiments, verifying its feasibility. Results: The proposed method had good results in the dynamic target grasping of collaborative robots, improving the accuracy of dynamic grasping. At a conveyor belt speed of 100 mm/s, the success rate of dynamic grasping reaches 99.50%, which had certain application value for food dynamic target grasping. Conclusion: By optimizing existing target grasping control methods, the grasping accuracy of collaborative robots can be effectively improved.