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Look Closer: Bridging Egocentric and Third-Person Views with Transformers for Robotic Manipulation. (arXiv:2201.07779v1 [cs.RO])
Jan. 20, 2022, 2:10 a.m. | Rishabh Jangir, Nicklas Hansen, Sambaral Ghosal, Mohit Jain, Xiaolong Wang
cs.LG updates on arXiv.org arxiv.org
Learning to solve precision-based manipulation tasks from visual feedback
using Reinforcement Learning (RL) could drastically reduce the engineering
efforts required by traditional robot systems. However, performing fine-grained
motor control from visual inputs alone is challenging, especially with a static
third-person camera as often used in previous work. We propose a setting for
robotic manipulation in which the agent receives visual feedback from both a
third-person camera and an egocentric camera mounted on the robot's wrist.
While the third-person camera is …
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