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.

翻译：本文提出SLOT（软体腿式全向四足机器人），一种采用3D打印TPU腿的肌腱驱动软体四足机器人，旨在研究仅使用四个执行器的顺应性腿式运动物理建模与控制。基于离散Cosserat杆理论将每条腿建模为可变形连续体，能够捕捉大弯曲变形、分布弹性、肌腱驱动及地面接触相互作用。引入模块化全身建模框架，其中顺应性腿部动力学通过作用于刚性躯干的物理一致反作用力表示，为连续体软肢与刚体运动动力学提供了可扩展接口。该公式可在不牺牲物理保真度的前提下实现高效的全身仿真与实时控制。所提出的模型被嵌入凸模型预测控制框架，该框架在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-角度关系将其映射至肌腱驱动。所得控制器在多种扰动下实现渐近稳定性。该框架在物理样机的爬行与步态行走中进行了实验验证，质心轨迹均方根误差小于5毫米，达到高精度控制。这些成果展示了将连续体软腿集成至基于模型的运动控制的通用方法，推进了软体四足机器人可扩展、可复用的建模与控制方法。