通过惠更斯耦合摆动力学突破四足机器人的速度缩放限制

中文摘要 AI 辅助

实现生物级别的奔跑速度主要通过控制算法的进步来追求，这些算法提高了现有硬件的利用率。然而，最终的速度极限仍受制于快速运动所需的基础力和力矩要求，这些要求通常通过增加执行器容量来解决。受惠更斯耦合摆的启发，我们证明，优越的运动能力可以源于对内在动力学的原理性利用，而非蛮力式的硬件缩放。肢体间的惯性耦合在步态周期中重新分配能量，并降低了快速周期运动所需的峰值关节力矩，从而在不按比例增加执行器能力的情况下扩大了可实现的速度。将硬件参数作为额外的设计变量纳入，进一步将这一分析扩展为协同优化框架，使得在机器人设计中系统性地利用惯性耦合成为可能。在该框架的指导下，一台四足机器人实现了10.74米/秒的奔跑速度（弗劳德数21.4），并在12.2秒内完成了100米短跑，成为首台速度超过10米/秒的足式机器人。这些结果确立了惯性耦合作为控制高速足式运动的基本机制，并强调了其在降低力需求方面的作用，为敏捷机器人系统的设计提供了新的见解。

英文摘要

Achieving biological-level running speeds has largely been pursued through advances in control algorithms, which improve the utilization of existing hardware. However, the ultimate speed limits remain governed by the underlying force and torque requirements of rapid locomotion, which are typically addressed through increased actuator capacity. Inspired by Huygens' coupled pendulums, we demonstrate that superior locomotion can emerge from principled exploitation of intrinsic dynamics rather than brute-force hardware scaling. Inter-limb inertial coupling redistributes energy across the gait cycle and reduces peak joint torque required for rapid periodic motion, thereby expanding the achievable speed without proportional increases in actuator capability. Incorporating hardware parameters as additional design variables further extends this analysis into a co-optimization framework, enabling the systematic utilization of inertial coupling in robot design. Guided by this framework, a quadruped robot achieves a running speed of 10.74 m/s (Froude number 21.4) and completes a 100-meter sprint in 12.2 seconds, representing the first legged robot to surpass 10 m/s. These results establish inertial coupling as an underlying mechanism governing high-speed legged locomotion and highlight its role in reducing force requirements, offering new insights into the design of agile robotic systems.

发表机构

• Center for X-Mechanics, Zhejiang University（浙江大学交叉力学中心）
• ZJU-Hangzhou Global Scientific and Technological Innovation Center（浙江大学杭州国际科创中心）
• Mirrorme Technology Co., Ltd.（魔镜科技有限公司）

机构由 AI 辅助整理，请以论文原文为准。