基于强化学习的智能机器人避碰方法研究

REINFORCEMENT-LEARNING-BASED OBSTACLE AVOIDANCE LEARNING FOR INTELLIGENT ROBOT

  • 摘要: 本文采用强化学习方法实现了智能机器人的避碰行为学习.文中首先介绍了强化学习原理,讨论了采用神经网络实现强化学习系统的方法,然后对具有强化学习机制的智能机器人避碰行为学习系统进行了仿真实验,并对仿真结果进行了分析.

     

    Abstract: Obstacle avoidance behavior learning of intelligent robot is realized by the use of reinforcement learning in this paper. First, the principle of reinforcement learning is introduced and the implement ation of reinforcement learning system is discussed. Then, the simulation experiments are carried out for obstacle avoidance learning system of intelligent robot that adopted reinforcement learning mechanism. Finally, the simulation results are analyzed.

     

/

返回文章
返回