The control method of industrial robot grasping structure based on deep reinforcement learning
Aiming at the shortcomings of traditional obstacle avoidance control methods in dynamic environments,a deep rein-forcement learning based industrial robot grasping and obstacle avoidance method is proposed.Build accurate environmental mod-els through deep reinforcement learning and use the A*algorithm to plan the optimal obstacle avoidance path to ensure path safety.Under the control of obstacle avoidance algorithms,the robot achieves stable grasping and real-time performance evaluation.Ex-perimental results have shown that this method improves the completion of grasping actions and the accuracy of obstacle avoidance paths,significantly reduces errors,and effectively enhances work efficiency and operational precision.
deep reinforcement learningindustrial robotgrasping structureobstacle avoidancecontrol
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