改进伺服执行器摩擦模型，提升机器人仿真真实度。
Extended Friction Models for the Physics Simulation of Servo Actuators
- 提出扩展摩擦模型，更精准捕捉伺服系统复杂动态。
- 在4种伺服电机上验证，2自由度机械臂仿真误差显著降低。
- 适合需要高精度仿真的机器人控制算法研发人员。
精确的物理仿真对机器人控制系统的设计与验证至关重要。近期强化学习研究广泛依赖大规模仿真生成高效控制策略，但当前主流伺服执行器模型难以捕捉其复杂的摩擦特性，限制了仿真结果向现实应用的迁移。本文提出一种扩展摩擦模型，通过全面分析多种摩擦模型，设计基于摆台实验轨迹的参数识别方法，并实现其在物理引擎中的集成。所提模型在4种不同伺服执行器上验证，并应用于2自由度机械臂，相比标准库仑-粘性模型，显著提升了仿真精度。结果表明，在伺服执行器仿真中考虑先进摩擦效应，可有效增强仿真真实性和可靠性。
原文摘要 · Abstract (English)
Accurate physical simulation is crucial for the development and validation of control algorithms in robotic systems. Recent works in Reinforcement Learning (RL) take notably advantage of extensive simulations to produce efficient robot control. State-of-the-art servo actuator models generally fail at capturing the complex friction dynamics of these systems. This limits the transferability of simulated behaviors to real-world applications. In this work, we present extended friction models that allow to more accurately simulate servo actuator dynamics. We propose a comprehensive analysis of various friction models, present a method for identifying model parameters using recorded trajectories from a pendulum test bench, and demonstrate how these models can be integrated into physics engines. The proposed friction models are validated on four distinct servo actuators and tested on 2R manipulators, showing significant improvements in accuracy over the standard Coulomb-Viscous model. Our results highlight the importance of considering advanced friction effects in the simulation of servo actuators to enhance the realism and reliability of robotic simulations.
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