Research and implementation of robot arm task imitation system based on RNN

摘要

In order to simplify the complex motion planning and improve the intelligence of robot arm, a robot arm task imitation system based on RNN (Recurrent Neural Network) is proposed. Firstly, the original task is demonstrated to robot arm, and the original data is collected which includes original task trajectory data and robot arm joint angle data. Secondly, RNN is constructed and used to obtain imitation policy by training original data. Thirdly, when task changes, new data is collected which only include new task trajectory data, and robot arm joint angle data is obtained by imitation policy generalization of new data. The experimental results show that the imitation system not only can simplify complex motion planning and reproduce demonstration of original task, but also can realize new task imitation by policy generalization when task changes.