QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation
arXiv: Learning, Volume abs/1806.10293, 2018, Pages 651-673.
In this paper, we study the problem of learning vision-based dynamic manipulation skills using a scalable reinforcement learning approach. We study this problem in the context of grasping, a longstanding challenge in robotic manipulation. In contrast to static learning behaviors that choose a grasp point and then execute the desired grasp...More
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