机器人用新方法打出专业级乒乓球发球，旋转速度超顶尖选手。
Ace! Motion Planning of Professional-Level Table Tennis Serves with a Robot Arm
- 结合运动基元、模型预测控制与贝叶斯优化生成发球
- 实现最高550 rad/s旋转、6.7 m/s速度，媲美甚至超越人类高手
- 适合对机器人精准控制和物理建模感兴趣的学者
乒乓球作为一项动态、紧凑且广受欢迎的运动，近年来成为机器人研究的重要基准。现有研究多聚焦于回击来球，需高速视觉、敏捷运动规划与闭环控制；而发球这一环节则鲜有探索，实则对物理建模与控制提出极高要求。机器人实现高水平发球面临特定挑战，如从无旋球产生高旋转、精准落点控制、多目标优化等。本文提出一种新方法，结合运动基元、模型预测控制（MPC）与贝叶斯优化，生成符合规则的发球动作。所生成发球可实现高达550 rad/s的旋转速度和6.7 m/s的球速，达到并超过顶级运动员水平。
原文摘要 · Abstract (English)
Table tennis, a dynamic, compact, and popular sport, has received significant attention as a robotics benchmark over the last decades. Most of the research has focused on the rally aspect - returning an incoming ball - requiring high-speed vision, agile motion planning, and tight closed-loop control. However, the other component of table tennis gameplay - the serve - is comparatively a quite unexplored research problem, that in fact requires pushing physics modeling and control to the extremes. Achieving competitive serves with a robot presents domain-specific challenges, such as high-spin generation from a spinless ball, precise aiming, or multi-objective optimization. In this work, we present a novel approach for generating official rule-compliant serves by combining motion primitives, Model Predictive Control, and Bayesian Optimization. Serves generated in this way offer a wide and controllable variation of spins of up to 550 rad/s, and speeds of up to 6.7 m/s, matching and even surpassing those of elite table tennis players.
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