首页 /研究 /Motion simulation of robot arm using reinforcement learning
LEARNING

Motion simulation of robot arm using reinforcement learning

Takahito Oshiro, Kajiro Watanabe

发表年份
2007
引用次数
2

摘要

This paper describes the learning of robot arm action by reinforcement learning. We used Q-learning, which is a typical method of reinforcement learning, and which was programmed via MATLAB software. Simulations demonstrated the shortest path of robot arm motion to reach the target location.

关键词

Reinforcement learningComputer scienceQ-learningRobotMotion (physics)Robotic armArtificial intelligenceRobot learningMATLABPath (computing)

相关论文

查看 LEARNING 分类全部论文