Reinforcement Learning Application in Teleoperation Training

Teleoperation technique is widely used in industrial automation, space, military, exploration and surgery. Considering the time delay in the operation and the high cost in fixing the problem. We can train the personnel remotely, so as to avoid the influence of delay. The traditional training mode, from the simplest way to train in an orderly way and step by step, can play an effect but will consume time too much. This paper discusses an adaptive intelligent system based on reinforcement learning. This system is based on zone of proximal development theory and uses reinforcement learning algorithm to train trainees in real time, so that trainees can keep in an efficient training mode.