SPARC让四足机器人脊柱兼具弯曲与伸缩，提升高速运动效率21%。
SPARC: Spine with Prismatic and Revolute Compliance for Quadruped Robots
- 设计可同时实现转动与伸缩的紧凑脊柱模块，支持独立调节刚度与阻尼。
- 高速运动时优化脊柱柔顺性可降低21%能耗，主要通过延长步幅和滤除高频扭矩波动。
- 适合研究仿生脊柱对四足机器人运动效率的影响，开源可用。
四足哺乳动物通过脊柱弯曲与轴向压缩协同提升运动敏捷性与效率。现有机器人脊柱通常缺乏支持此类动态行为所需的主动柔顺性。本文提出SPARC，一个紧凑的3自由度矢状面脊柱模块，在1.26公斤质量下实现转动与伸缩运动。通过浮基阻抗控制器，可在任务空间独立调节脊柱刚度与阻尼，模拟生物负载策略。台架实验验证了高保真阻抗响应，力-位移误差线性度优于1.5%。系统性运动仿真表明：低速时脊柱特性对效率影响不显著，但高速时精确阻抗调节至关重要。结果表明，最优柔顺脊柱在0.9米/秒速度下相比刚性脊柱节能21%，机制在于增加步幅长度并作为机械低通滤波器抑制高频扭矩波动。SPARC提供开放源代码平台，用于系统研究腿式机器人脊柱柔顺性的作用。项目地址：github.com/YueWang996/sparc
原文摘要 · Abstract (English)
Quadruped mammals coordinate spinal bending and axial compression to enhance locomotion agility and efficiency. However, existing robotic spines typically lack the active compliance required to support such dynamic behaviours. We present SPARC, a compact 3-DoF sagittal-plane spine module that enables simultaneous revolute and prismatic motions within a 1.26 kg package. Using a floating-base impedance controller, we facilitate independent, task-space tuning of spinal stiffness and damping to mimic biological load-bearing strategies. Benchtop experiments confirm high-fidelity rendering of commanded impedance, with linear force-displacement error within 1.5%. Systematic locomotion simulations reveal a critical speed-dependency: while low-speed efficiency is insensitive to spinal properties, precise impedance tuning becomes indispensable for high-speed performance. Our results demonstrate that an optimally compliant spine reduces power consumption by 21% at 0.9 m/s compared to a rigid-spine baseline. This efficiency gain is mechanistically attributed to the spine's role in augmenting stride length and acting as a mechanical low-pass filter to attenuate high-frequency torque fluctuations. SPARC provides an open-source platform for systematic studies of spine compliance in legged locomotion. Available at: github.com/YueWang996/sparc
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