arXiv:2602.16371cs.RO2026-02

用四根腱驱动软腿实现稳定爬行,物理模型精准控制机器人运动

Dynamic Modeling and MPC for Locomotion of Tendon-Driven Soft Quadruped

  • 用离散柯西杆理论建模软腿变形,结合腱驱动和地面接触力
  • 实测重心轨迹误差小于5毫米,0.495秒预测期内实现稳定行走
  • 适合做软体四足机器人的模型与控制研究,可扩展性强

SLOT(软腿全向四足机器人)是一种由3D打印TPU材料制成的腱驱动软体四足机器人,仅使用四个执行器研究基于物理约束的柔顺腿运动建模与控制。每条腿采用离散柯西杆理论建模为可变形连续体,能捕捉大弯曲变形、分布弹性、腱驱动及地面接触相互作用。提出模块化全身建模框架,通过物理一致的反作用力将柔顺腿动力学映射至刚性躯干,实现连续体软肢与刚体运动动力学间的高效可扩展接口。该方法在保持物理保真度的同时支持全系统仿真与实时控制。所提模型嵌入凸型模型预测控制框架,在0.495秒预测时域内优化地面反作用力,并通过物理启发的力-角关系将其映射为腱驱动指令。控制器在多种扰动下实现渐近稳定。在实体原型上验证了爬行与步行步态,重心轨迹均方根误差低于5毫米。结果表明该方法通用性强,为集成连续体软腿提供了可复用的建模与控制范式。

原文摘要 · Abstract (English)

SLOT (Soft Legged Omnidirectional Tetrapod), a tendon-driven soft quadruped robot with 3D-printed TPU legs, is presented to study physics-informed modeling and control of compliant legged locomotion using only four actuators. Each leg is modeled as a deformable continuum using discrete Cosserat rod theory, enabling the capture of large bending deformations, distributed elasticity, tendon actuation, and ground contact interactions. A modular whole-body modeling framework is introduced, in which compliant leg dynamics are represented through physically consistent reaction forces applied to a rigid torso, providing a scalable interface between continuum soft limbs and rigid-body locomotion dynamics. This formulation allows efficient whole-body simulation and real-time control without sacrificing physical fidelity. The proposed model is embedded into a convex model predictive control framework that optimizes ground reaction forces over a 0.495 s prediction horizon and maps them to tendon actuation through a physics-informed force-angle relationship. The resulting controller achieves asymptotic stability under diverse perturbations. The framework is experimentally validated on a physical prototype during crawling and walking gaits, achieving high accuracy with less than 5 mm RMSE in center of mass trajectories. These results demonstrate a generalizable approach for integrating continuum soft legs into model-based locomotion control, advancing scalable and reusable modeling and control methods for soft quadruped robots.

软体机器人模型预测控制腱驱动运动规划

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