双柔性7自由度手臂机器人像孩子一样学习使用Q-learning跳舞

Sulabh Kumra, F. Sahin
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引用次数: 3

摘要

研究人员和学者们做了许多尝试,让人们对机器人更熟悉。其中一个例子就是娱乐机器人的舞蹈表演。在大多数情况下,为机器人编程舞蹈动作并使其同步是一项艰巨的挑战。此外,预编程的舞蹈动作和同步信息只对特定的音乐轨道有用,对其他任何音乐轨道都没用。为了解决这些问题,我们开发了一个新的系统,可以让机器人根据输入的音乐轨迹学习舞蹈动作。该系统主要由两部分组成:第一部分是音乐音轨的节拍提取系统;第二个是为巴克斯特学习舞蹈动作的系统。在第一部分中,使用STFT对音轨进行分析,并计算峰间时间。这给出了给定音乐轨道的每分钟节拍数(BPM)。第二部分将音轨的BPM和持续时间输入到开发的Q-learning算法中,让Baxter学习舞蹈动作,并将舞蹈动作与节拍同步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dual flexible 7 DoF arm robot learns like a child to dance using Q-learning
Many attempts have been made by researchers and scholars to make people feel more conversant to robots. One such example is the dance performance of an Entertainment Robot. In most cases, the challenge to program dance motions for a robot and synchronize them has been too heavy. In addition, pre-programmed dance moves and synchronization information are useful only for a specific music track and are useless for any other. To solve these problems, we developed a new system that can make a robot learn dance moves according to the input music track. The system comprises of two main parts: the first is a beat extraction system for music track; and the second one is a system that learns dance motion for Baxter. In the first part, music track is analyzed using STFT and peak-to-peak time duration is computed. This gives the beats per minute (BPM) of the given music track. The second part takes the BPM and duration of track and feeds it to the developed Q-learning algorithm to make Baxter learn dance moves and synchronize dance motion to beat rate.
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