Jiang Lei, Fu Chaojie, Liang Yanhong, Jin Yongbin, Wang Hongtao
Center for X-Mechanics, Zhejiang University, Hangzhou, China.
ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, China.
Front Neurorobot. 2025 Jan 30;18:1513458. doi: 10.3389/fnbot.2024.1513458. eCollection 2024.
Dexterous hands play vital roles in tasks performed by humanoid robots. For the first time, we quantify the correlation between design variables and the performance of 65 dexterous hands using Cramér's V. Comprehensive cross-correlation analysis quantitatively reveals how the performance, such as speed, weight, fingertip force, and compactness are related to the design variables including degrees of freedom (DOF), structural form, driving form, and transmission mode. This study shows how various design parameters are coupled inherently, leading to compromise in performance metrics. These findings provide a theoretical basis for the design of dexterous hands in various application scenarios and offer new insights for performance optimization.
灵巧手在人形机器人执行的任务中发挥着至关重要的作用。我们首次使用克莱姆V系数量化了65种灵巧手的设计变量与性能之间的相关性。全面的交叉相关性分析定量地揭示了诸如速度、重量、指尖力和紧凑性等性能如何与包括自由度(DOF)、结构形式、驱动形式和传动模式在内的设计变量相关。本研究展示了各种设计参数是如何内在耦合的,从而导致性能指标的折衷。这些发现为各种应用场景下灵巧手的设计提供了理论基础,并为性能优化提供了新的见解。