提出接触一致的动力学归一化方法，提升人机交互中机器人的稳定性与精度。
Contact-Consistent Interaction Dynamics Normalization for Predictive Physical Human--Robot Interaction
- 用加速度坐标下的线性双积分器表示末端执行器残差通道
- 在接触切换和支撑模式变化时实现近零偏移跟踪
- 适合需要高精度物理交互的足式机器人应用
在浮根基座机器人上实现安全的物理人机交互，需在接触约束变化时进行交互调节。本文提出一种接触一致的归一化方法，将末端执行器残差通道表示为加速度坐标下的线性双积分器。离散预测矩阵与构型和支撑模式无关，姿态与接触仅通过任务惯性力恢复和约束引入。控制器结合恒海森堡递推优化问题、加速度扰动观测器及优先级一致实现方式。经典操作空间阻抗被证明是无约束无限时域极限情形。在17自由度双足机器人和基于Menagerie的Unitree G1模型上，通过MuJoCo实验评估持续受力、传递冲击及计划中的接触模型切换。观测器在真实接触集切换和计划支撑模式转换中保持近零偏移跟踪；扰动估计而非接触一致性本身，是固定支撑精度的主要来源；协方差膨胀仅在特定场景下带来瞬态收益。
原文摘要 · Abstract (English)
Safe physical human--robot interaction on floating-base robots requires interaction regulation under changing contact constraints. We develop a contact-consistent normalization in which the residual end-effector channel is represented as a linear double integrator in acceleration coordinates. Both discrete prediction matrices are independent of configuration and support mode; posture and contact enter only through task-inertia force recovery and constraints. The controller combines a constant-Hessian receding-horizon QP, an acceleration-disturbance observer, and a priority-consistent realization. Classical operational-space impedance is shown to be the unconstrained infinite-horizon limit. MuJoCo experiments on a 17-DOF biped and a Menagerie-derived Unitree G1 model evaluate sustained forces, transmitted shocks, and scheduled contact-model changes. The observer sustains near-offset-free tracking across a genuine contact-set switch and a scheduled support-mode transition, while disturbance estimation---not contact consistency alone---is the dominant source of fixed-stance accuracy; covariance inflation gives only scenario-dependent transient benefit.
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