Reinforcement learning-based distributed impedance control of robots for compliant operation in tight interaction tasks

摘要

It is challenging to achieve compliant operation in tight interaction tasks, where closed-loop constraints are formed between the robots or between a robot and the environment. Complex dynamic interactions and uncertain parameters degrade the performance of model-based controllers. In this paper, a reinforcement learning-based distributed impedance control approach is proposed for these tight interaction tasks. Two aspects are considered to ensure compliant operation for the robots. First, a distributed impedance model is established through the design of reasonable independence states and nodes networks. Second, the reinforcement learning agent is designed to make decision for adjusting impedance parameters . The trained parameters are integrated into the designed impedance model, and a model-based controller is then employed for compliant control for the robots. The effectiveness is validated under two different tight interaction scenarios via co-simulation. Compliant operation can be achieved whether between robots or between a robot and the environment. • An RL-based distributed impedance method is proposed for force-position compliance control of robot in tightly interacting tasks, where a closed-chain contact should be maintained between the robots or between the robot and the environment. • The designed distributed impedance model can describe the dynamic characteristics. Whether it is a single robot or a multi-robot closed-loop constraint system, this makes the method more extensible. Additionally, the integration of the RL agents enable better fitting of impedance parameters. • From a practical point of view, different scenarios and various factors are considered in simulations. The robot can accomplish the desired tightly interacting tasks in a co-simulation platform between MATLAB and Coppeliasim. The results demonstrate the effectiveness of the proposed RL-based distributed impedance control method.