发表机构
Sony AI, Tokyo, Japan; Sony AI, Zürich, Switzerland; Sony Group Corporation, Tokyo, Japan（索尼人工智能，东京，日本; 索尼人工智能，苏黎世，瑞士; 索尼集团公司，东京，日本）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究乒乓球机器人发球问题，结合运动原语、模型预测控制和贝叶斯优化方法，实现符合官方规则发球，自旋高达550rad/s，速度达6.7m/s，表现与精英球员相当甚至更优。
AI 中文摘要
乒乓球是一项充满活力、紧凑且广受欢迎的运动，在过去几十年里作为机器人技术基准受到了广泛关注。以往研究大多集中在回合方面，而乒乓球比赛的发球环节相对未被充分探索，它对物理建模和控制要求极高。用机器人实现具有竞争力的发球面临诸多特定领域挑战。本文提出一种新方法，通过结合运动原语、模型预测控制和贝叶斯优化来生成符合官方规则的发球。这样生成的发球具有高达550弧度/秒的自旋和高达6.7米/秒的速度，其自旋变化范围广且可控，与精英乒乓球运动员的表现相当甚至更优。
英文摘要
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.
Comments8 pages, 4 figures
