Model-based Q-learning for humanoid robots

Than D. Le, An T. Le, D. Nguyen
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引用次数: 9

Abstract

This paper is proposal with regarding reinforcement learning and robotics. It contains our study so far about reinforcement learning problem and Q-learning — one of the methods to solve it. The method is tested both by running on a simulation and on NAO robot. Both are written in high programming language. Since the testing are also done on NAO robot. This paper also includes our understanding about NAO robot and Robotic Operating System (ROS), and our approach to apply Q-learning on NAO robot. In the end, we have been successfully tested Q-learning method and apply it to NAO robot in real-world environment.
基于模型的类人机器人q学习
本文是关于强化学习和机器人技术的一些建议。它包含了我们迄今为止关于强化学习问题和q学习的研究——解决它的方法之一。通过仿真和NAO机器人对该方法进行了验证。两者都是用高级编程语言编写的。因为测试也是在NAO机器人上进行的。本文还介绍了我们对NAO机器人和机器人操作系统(ROS)的理解,以及我们在NAO机器人上应用Q-learning的方法。最后,我们成功地测试了Q-learning方法,并将其应用于NAO机器人的实际环境中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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