arXiv:2505.24860cs.RO2025-05

用花生酱做阻尼器,让仿生机械手更像人手抓物更稳。

PB&J: Peanut Butter and Joints for Damped Articulation

  • 用花生酱模拟人体关节的黏弹性,实现自适应阻尼。
  • 加入弹性结构后,手指能同步弯曲并稳定抓握球体。
  • 低成本开源平台,适合研究生物力学与机器人控制。

许多仿生机器人模仿人类手部刚性关节结构进行抓取任务,但会因高频机械扰动导致系统失稳,影响精度。尽管控制器带宽有限且存在感测与执行的时间延迟,生物系统仍能有效响应并缓解这些扰动。人类关节具有阻尼和刚度特性,而多数刚性仿生手缺乏此类属性。为探索关节黏弹性对控制的影响,我们开发了一款受人手启发的抓取机器人,采用可获取且生物来源材料构建黏弹性结构,降低原型设计的经济与环境成本。实验表明,手指关节处的弹性元件是实现同步屈曲、安全抓握球形物体的必要条件。为显著抑制制造出的手指关节振动,我们建模、制作并表征了以花生酱作为有机类关节工作流体的旋转阻尼器。最终,我们证明基于位置的实时控制器能够成功捕捉轻质下落小球。该开源、低成本抓取平台抽象了人手的形态与力学特性,使研究人员得以在真实系统中探索原本难以通过仿真或建模验证的生物力学问题。

原文摘要 · Abstract (English)

Many bioinspired robots mimic the rigid articulated joint structure of the human hand for grasping tasks, but experience high-frequency mechanical perturbations that can destabilize the system and negatively affect precision without a high-frequency controller. Despite having bandwidth-limited controllers that experience time delays between sensing and actuation, biological systems can respond successfully to and mitigate these high-frequency perturbations. Human joints include damping and stiffness that many rigid articulated bioinspired hand robots lack. To enable researchers to explore the effects of joint viscoelasticity in joint control, we developed a human-hand-inspired grasping robot with viscoelastic structures that utilizes accessible and bioderived materials to reduce the economic and environmental impact of prototyping novel robotic systems. We demonstrate that an elastic element at the finger joints is necessary to achieve concurrent flexion, which enables secure grasping of spherical objects. To significantly damp the manufactured finger joints, we modeled, manufactured, and characterized rotary dampers using peanut butter as an organic analog joint working fluid. Finally, we demonstrated that a real-time position-based controller could be used to successfully catch a lightweight falling ball. We developed this open-source, low-cost grasping platform that abstracts the morphological and mechanical properties of the human hand to enable researchers to explore questions about biomechanics in roboto that would otherwise be difficult to test in simulation or modeling.

仿生机器人黏弹性花生酱抓取控制

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