Robotic Table Tennis: A Case Study into a High Speed Learning System

We present a deep-dive into a real-world robotic learning system that, in previous work, was shown to be capable of hundreds of table tennis rallies with a human and has the ability to precisely return the ball to desired targets. This system puts together a highly optimized perception subsystem, a...

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Veröffentlicht in:	arXiv.org 2023-09
Hauptverfasser:	D'Ambrosio, David B, Abelian, Jonathan, Abeyruwan, Saminda, Ahn, Michael, Bewley, Alex, Boyd, Justin, Choromanski, Krzysztof, Cortes, Omar, Coumans, Erwin, Ding, Tianli, Gao, Wenbo, Graesser, Laura, Iscen, Atil, Jaitly, Navdeep, Jain, Deepali, Kangaspunta, Juhana, Kataoka, Satoshi, Kouretas, Gus, Kuang, Yuheng, Lazic, Nevena, Lynch, Corey, Mahjourian, Reza, Moore, Sherry Q, Nguyen, Thinh, Oslund, Ken, Reed, Barney J, Reymann, Krista, Sanketi, Pannag R, Shankar, Anish, Sermanet, Pierre, Sindhwani, Vikas, Singh, Avi, Vanhoucke, Vincent, Vesom, Grace, Xu, Peng
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Computer Science - Robotics Damage prevention Human performance Parameter sensitivity Perception Robot learning Robots Subsystems Tennis Training
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