提出新型步态模型，让双足机器人在不平地面行走更稳。
Bipedal Robust Walking on Uneven Footholds: Piecewise Slope LIPM with Discrete Model Predictive Control
- 用分段坡度LIPM动态调节重心高度适应地形起伏。
- 结合角动量控制，实现步态参数的联合优化。
- 适合研究机器人步态控制与复杂地形导航的学者。
本研究针对不平整地形下双足机器人的运动控制问题，提出改进的分层控制框架。由于传统线性倒立摆模型（LIPM）难以处理地形高程变化，本文提出分段坡度LIPM（PS-LIPM），可在单步周期内动态调整质心（CoM）高度以匹配地形起伏。同时，提出基于角动量的广义LIPM（G-ALIP），通过质心角动量（CAM）调控实现质心速度补偿。在此基础上，推导出用于模型预测控制（MPC）的质心偏移量（DCM）步间动力学方程，实现步位与步长的联合优化。构建了融合MPC与全身控制器（WBC）的分层控制框架，在不规则踏石地形上实现了稳定双足行走。实验验证了所提理论框架与控制策略的有效性。
原文摘要 · Abstract (English)
This study presents an enhanced theoretical formulation for bipedal hierarchical control frameworks under uneven terrain conditions. Specifically, owing to the inherent limitations of the Linear Inverted Pendulum Model (LIPM) in handling terrain elevation variations, we develop a Piecewise Slope LIPM (PS-LIPM). This innovative model enables dynamic adjustment of the Center of Mass (CoM) height to align with topographical undulations during single-step cycles. Another contribution is proposed a generalized Angular Momentum-based LIPM (G-ALIP) for CoM velocity compensation using Centroidal Angular Momentum (CAM) regulation. Building upon these advancements, we derive the DCM step-to-step dynamics for Model Predictive Control MPC formulation, enabling simultaneous optimization of step position and step duration. A hierarchical control framework integrating MPC with a Whole-Body Controller (WBC) is implemented for bipedal locomotion across uneven stepping stones. The results validate the efficacy of the proposed hierarchical control framework and the theoretical formulation.
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