通过模拟器端动力学归一化，显著缩小并联腿机构仿真与实物的差距。
Bridging the Sim-to-Real Gap in Parallel-Link Leg Mechanisms via Simulator-Side Dynamics Normalization
- 在仿真中对串树模型进行坐标变换，归一化执行器惯性与阻尼影响。
- 验证中关节位置和力矩误差降低超80%，地面反作用力误差减少65%以上。
- 适合做机器人运动控制仿真训练，尤其关注高保真物理建模的研究者。
本文针对并联腿机构在使用串联树替代模型进行仿真时出现的动力学仿真-现实差距问题。传统基于雅可比矩阵的状态与力矩映射虽保持运动学与虚功关系一致性，但未考虑坐标变换导致的执行器惯性与阻尼重分布，以及串联化过程中忽略的连杆惯性。为此，提出模拟器端系统归一化（S3N）方法，在保持树状拓扑的前提下归一化串联模型的有效动力学。S3N-Act通过坐标变换将执行器惯性与阻尼纳入串坐标动力学；S3N-Full则通过分别识别执行器级与腿级频率响应来恢复残余连杆惯性。2-自由度验证中，相较于雅可比映射基线，S3N-Full使关节位置和扭矩均方根误差分别降低80.9%和82.1%。在原地俯仰运动中，S3N-Act与S3N-Full使地面反作用力幅值的均方根误差分别减少65.1%和62.4%。在圆周行走运动中，相位平均、指令归一化的仿真-现实差距从17.3%降至9.9%。结果表明，模拟器端归一化有效提升运动与受力层面的仿真-现实一致性，支持在串联树框架下进行硬件一致的动力学策略训练，更真实地表征物理并联腿机构。
原文摘要 · Abstract (English)
This paper addresses the sim-to-real gap in dynamics arising when a parallel-link mechanism is represented by a serial-tree surrogate in simulation. Conventional Jacobian-based state and torque mappings preserve consistency with the kinematic and virtual-work relations but do not account for the coordinate-induced redistribution of actuator inertia and damping and the linkage inertia omitted during serial-tree reduction. To address this gap, Simulator-Side System Normalization (S3N) is proposed to normalize the serial-tree simulator's effective dynamics while preserving its tree topology. S3N-Act incorporates actuator inertia and damping into the serial-coordinate dynamics through coordinate transformation, whereas S3N-Full restores residual linkage inertia by separately identifying actuator- and leg-level frequency responses. In the 2-DoF validation, S3N-Full reduced the joint-position and torque RMSEs by 80.9% and 82.1%, respectively, relative to the Jacobian-mapping baseline. During pitch-in-place motion, S3N-Act and S3N-Full reduced the RMSE of the ground reaction force norm by 65.1% and 62.4%, respectively. During circular locomotion, S3N-Full reduced the phase-averaged, command-normalized sim-to-real gap from 17.3% to 9.9%. These results show that simulator-side normalization improves motion- and force-level sim-to-real consistency. It enables policy training in a serial-tree framework with hardware-consistent dynamics that better represent the physical parallel-link mechanism.
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