Reinforcement learning based obstacle avoidance for robotic manipulator
Shiqi Li · Machinery Design and Manufacture · 2007
This paper reports on the obstacle avoidance problem for robotic manipulators.The reinforcement learning(RL)method was applied to obstacle avoidance problem and a multi-agent system was built.According the real-time demand of manipulator control,the Sarsa(λ)algorithm,which was combined with K-means clustering algorithm,has been selected for its on-policy feature and efficiency.The implement process of the algorithm was given and in the end of this paper,a simulation experiment with different environment was done,the result showed the RL method's feasibility and availability.