多指机器人手的灵巧性基准测试：综述与展望
Benchmarking Dexterity of Multifingered Robot Hands: A Review and Perspective
- US National Science Foundation HAND Engineering Research Center（美国国家科学基金会HAND工程研究中心）
- Center for Robotics and Biosystems, Northwestern Univ.（西北大学机器人与生物系统中心）
- Department of Mechanical Engineering, Texas A&M Univ.（德克萨斯A&M大学机械工程系）
- Department of Electrical and Computer Engineering, Carnegie Mellon Univ.（卡内基梅隆大学电子与计算机工程系）
- Department of Mechanical Engineering, Florida A&M Univ.（佛罗里达A&M大学机械工程系）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文综述多指机器人手灵巧性基准测试，提出三层级框架并建议新基准与指标，以促进物理人工智能发展。
AI中文摘要：
机器人手是人工智能与物理世界之间的关键接口，推动机器人灵巧性的进步对于实现物理人工智能的愿景至关重要。尽管简单的夹持器已展现出令人印象深刻的灵巧性，但多指手在操作中提供了实现显著更高通用性、精确性和适应性的潜力。在这篇综述中，我们调研了多指机器人手灵巧性基准测试的最新进展。认识到灵巧性是一个复杂且多层面的概念，我们提出了美国国家科学基金会HAND工程研究中心的观点，特别关注精细的手内操作。我们引入了一个由三个基准层级组成的框架，这些层级对应于系统复杂性的增加，回顾了每个层级的代表性基准，并提出了新的基准和指标以解决文献中的局限性。更多信息可参见此https URL。
英文摘要：
Robot hands are a key interface between AI and the physical world, making advances in robotic dexterity essential to realizing the vision of physical AI. While impressive dexterity has been demonstrated with simple grippers, multifingered hands offer the potential for substantially greater versatility, precision, and adaptability in manipulation. In this review, we survey the state of the art in benchmarking the dexterity of multifingered robot hands. Recognizing dexterity as a complex and multifaceted concept, we present the perspective of the U.S. National Science Foundation HAND Engineering Research Center, with a particular focus on fine in-hand manipulation. We introduce a framework consisting of three benchmark levels that correspond to increasing system complexity, review representative benchmarks at each level, and propose new benchmarks and metrics to address limitations in the literature. More information can be found at https://hand-erc.github.io/benchmarking/.
