Mobile Grasping Robot Trajectory under Reinforcement Learning Applications
Reinforcement learning is a machine learning method that learns optimal behavior through interaction between agents and the environment.In the field of mobile grasping robots,reinforcement learning algorithms can be used to optimize robot trajectories,improve their grasping efficiency and obstacle avoidance ability.This article introduces the application of reinforcement learning algorithms in trajectory optimization of mobile grasping robots,and its effectiveness was verified through experiments.
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