伯克利QUAD手：一种用于灵巧高效抓取与操作的准直驱欠驱动非对称手

中文摘要 AI 辅助

本文介绍了伯克利QUAD（准直驱、欠驱动、非对称设计）手，这是一种具有11个自由度和8个驱动自由度的四指拟人手。该设计在每个手指的基部采用准直驱（QDD）驱动，实现了高力透明性，从而支持灵巧的自适应操作。然而，这类执行器固有的低扭矩密度传统上在尺寸、重量和热限制方面带来主要问题。我们通过应用仿生非对称性克服了这一问题：将灵巧性分配给桡侧手指，通过独立的QDD驱动实现；将力量分配给尺侧手指，通过由较大QDD电机驱动的欠驱动、柔顺耦合传动实现。一种新颖的预紧连杆传动机构实现了这种尺侧耦合，同时保持了类似人类的工作空间可达性。在轻负载下，尺侧电机直接驱动第三（中指）手指以实现灵巧性，而第四（无名指）手指则镜像其运动。然而，在较大负载下，中指顺应弯曲，而电机驱动无名指进一步向下并向抓取中心内收，以施加更好的闭合力。硬件评估验证了该架构，结果表明该手实现了Feix分类法中33种抓取中的29种，并且反向驱动力低至50克，适用于精细交互。此外，欠驱动的第四手指改善了抓取闭合性，并为更大的驱动提供了必要的空间效率，在持续负载下实现了高达96倍的发热量减少。网页：https://benudavis.github.io/berkeley-quadhand/

英文摘要

In this paper, we present the Berkeley QUAD (Quasi-direct-drive, Underactuated, Asymmetric Design) Hand, a four-finger anthropomorphic robotic hand with 11 degrees of freedom and 8 degrees of actuation. The design utilizes QDD actuation at the base of each finger, enabling high force transparency for dexterous, adaptive performance. However, the low torque density of these actuators traditionally presents major issues with size, weight, and thermal limits. We overcome this by applying bio-inspired asymmetry, delegating dexterity to the radial fingers through individual QDD actuation, and strength to the ulnar finger through an underactuated, compliantly coupled transmission driven by a larger QDD motor. A novel preloaded, linkage-based transmission permits this ulnar coupling in a way that preserves human-like workspace reachability. Under light loads, the ulnar motor drives the third (middle) finger directly for dexterity while the fourth (ring) finger mirrors its motion. However, under larger loads, the middle finger complies while the motor drives the ring finger further downwards and inwards toward the center of the grasp to apply better closure forces. Hardware evaluations validate this architecture, demonstrating that the hand achieves 29 out of 33 Feix taxonomy grasps and exhibits backdrive forces as low as 50 g for delicate interactions. Additionally, the underactuated fourth finger improves grasp closure and provides the spatial efficiency necessary for larger actuation, yielding up to a 96-fold reduction in heat generation during sustained loading. Webpage: https://benudavis.github.io/berkeley-quadhand/

发表机构

• University of California Berkeley（加州大学伯克利分校）
• General Motors（通用汽车公司）

机构由 AI 辅助整理，请以论文原文为准。