Extended Friction Models for the Physics Simulation of Servo Actuators

2024-10-11

arXiv.org

AI Summary

Existing servo actuator simulations employ coarse friction models (e.g., classical Coulomb-viscous approximations), leading to poor sim-to-real transfer. This work proposes an extended friction model that systematically integrates the Stribeck effect, LuGre hysteresis, and dynamic state evolution—marking the first unified formulation enabling fully automated, trajectory-driven parameter identification from real pendulum-arm motion data. The model features a plug-and-play interface compatible with mainstream physics engines. Evaluated on four servo motors and a 2R manipulator, it reduces mean position and velocity prediction errors by 62% over baseline models and significantly improves cross-domain control policy transfer success. This work establishes a reproducible, deployable friction modeling paradigm for high-fidelity robotic dynamics simulation.

Technology Category

• Intelligent Robots: State Estimation
• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior
• Humans and AI: Human-Aware Planning and Behavior Prediction

Application Category

• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

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.

Problem

• Accurate simulation of servo actuator friction dynamics.
• Improving transferability of simulated behaviors to real-world applications.
• Enhancing realism and reliability of robotic simulations.

Innovation

• Extended friction models for servo actuators.
• Parameter identification using pendulum test bench.
• Integration of advanced friction models into physics engines.