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Computer Science > Robotics

arXiv:2311.06543 (cs)
[Submitted on 11 Nov 2023]

Title:Bootstrapping Robotic Skill Learning With Intuitive Teleoperation: Initial Feasibility Study

Authors:Xiangyu Chu, Yunxi Tang, Lam Him Kwok, Yuanpei Cai, Kwok Wai Samuel Au
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Abstract:Robotic skill learning has been increasingly studied but the demonstration collections are more challenging compared to collecting images/videos in computer vision and texts in natural language processing. This paper presents a skill learning paradigm by using intuitive teleoperation devices to generate high-quality human demonstrations efficiently for robotic skill learning in a data-driven manner. By using a reliable teleoperation interface, the da Vinci Research Kit (dVRK) master, a system called dVRK-Simulator-for-Demonstration (dS4D) is proposed in this paper. Various manipulation tasks show the system's effectiveness and advantages in efficiency compared to other interfaces. Using the collected data for policy learning has been investigated, which verifies the initial feasibility. We believe the proposed paradigm can facilitate robot learning driven by high-quality demonstrations and efficiency while generating them.
Comments: 10 pages, 4 figures, accepted by ISER2023
Subjects: Robotics (cs.RO)
Cite as: arXiv:2311.06543 [cs.RO]
  (or arXiv:2311.06543v1 [cs.RO] for this version)
  https://doi.org/10.48550/arXiv.2311.06543

Submission history

From: Xiangyu Chu [view email]
[v1] Sat, 11 Nov 2023 11:37:46 UTC (1,728 KB)
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