用吸盘手指的机械手实现单手完成复杂操作,突破人类手部局限。
Suction Leap-Hand: Suction Cups on a Multi-fingered Hand Enable Embodied Dexterity and In-Hand Teleoperation
- 在多指手上集成吸盘,用单点吸附替代复杂抓握。
- 可稳定完成单手剪纸、执笔书写等人类难以做到的动作。
- 适合需要高精度单手操作的工业或服务机器人场景。
灵巧的物体手中操控仍是机器人领域的一项基础挑战,现有进展常受限于模仿人类手部结构的范式。这种类人设计带来两大障碍:一是将机器人能力局限于人类已能完成的任务,二是使基于学习的方法数据收集极为困难。根本原因在于传统力闭合抓取需依赖摩擦力、法向力和重力协调多点接触,导致遥操作演示不稳定,并加剧强化学习中的仿真到现实差距。本文提出范式转变:摆脱对人类力学结构的模仿,转向新型机器人本体设计。我们提出Suction Leap-Hand(SLeap Hand),一种配备指尖吸盘的多指机械手,实现新型吸力驱动的灵巧操作。通过以稳定的单点吸附取代复杂的力闭合抓取,该设计从根本上简化了手中遥操作,并促进高质量示范数据的采集。更重要的是,这种吸力驱动的本体解锁了一类人类手部难以甚至无法实现的灵巧技能,如单手剪纸和手中书写。研究证明,突破类人限制后,新颖的本体不仅能降低可靠操控数据的获取门槛,还能实现通常需双手协作的任务的单手稳定完成。
原文摘要 · Abstract (English)
Dexterous in-hand manipulation remains a foundational challenge in robotics, with progress often constrained by the prevailing paradigm of imitating the human hand. This anthropomorphic approach creates two critical barriers: 1) it limits robotic capabilities to tasks humans can already perform, and 2) it makes data collection for learning-based methods exceedingly difficult. Both challenges are caused by traditional force-closure which requires coordinating complex, multi-point contacts based on friction, normal force, and gravity to grasp an object. This makes teleoperated demonstrations unstable and amplifies the sim-to-real gap for reinforcement learning. In this work, we propose a paradigm shift: moving away from replicating human mechanics toward the design of novel robotic embodiments. We introduce the \textbf{S}uction \textbf{Leap}-Hand (SLeap Hand), a multi-fingered hand featuring integrated fingertip suction cups that realize a new form of suction-enabled dexterity. By replacing complex force-closure grasps with stable, single-point adhesion, our design fundamentally simplifies in-hand teleoperation and facilitates the collection of high-quality demonstration data. More importantly, this suction-based embodiment unlocks a new class of dexterous skills that are difficult or even impossible for the human hand, such as one-handed paper cutting and in-hand writing. Our work demonstrates that by moving beyond anthropomorphic constraints, novel embodiments can not only lower the barrier for collecting robust manipulation data but also enable the stable, single-handed completion of tasks that would typically require two human hands. Our webpage is https://sites.google.com/view/sleaphand.
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