Teaching and reinforcement learning of robotic view-based manipulation
Teaching and reinforcement learning of robotic view-based manipulation
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DOI：
10.1109/roman.2013.6628454
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发表时间：
2013-10
期刊：
影响因子：
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通讯作者：
Y. Maeda;Ryohei Aburata
中科院分区：
文献类型：
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作者：
Y. Maeda;Ryohei Aburata
作者研究了“基于视图的教学/回放”：一种基于视图的图像处理的机器人编程方法，它可以比传统的教学/回放方案更好地适应任务条件的变化。强化学习与这种方法相结合，使必要的人类教学最少，并且在我们之前的研究中将其应用于虚拟环境中的机器人操作。然而，在线强化学习的过程需要大量的计算时间。此外，强化学习的低成功率使得学习成功的预期时间更长。因此，我们加快了强化学习的过程中，在本文中，使我们提出的方法更实用。我们还试图提高强化学习的成功率，以进一步加速学习。
The authors study “view-based teaching/playback”: a method of robot programming with view-based image processing which can achieve more robustness against changes of task conditions than the conventional teaching/playback scheme. Reinforcement learning was integrated with this method to make necessary human teaching minimal and it was applied to robotic manipulation in a virtual environment in our previous study. However, the process of online reinforcement learning requires huge computation time. Moreover, the low success rate of reinforcement learning makes the expected time to learning success longer. Thus we accelerate the process of reinforcement learning in this paper to make our proposed method more practical. We also try to improve the success rate of reinforcement learning for further learning acceleration.