Improving Back-drivability of Robot Joint by Reducing Reflected Inertia Using Multi-motor System

摘要

Enhancing back-drivability in robot joints is crucial for safe and effective physical human-robot interaction (pHRI). This paper presents a novel approach to improve back-drivability by reducing reflected inertia through a multi-motor system (MMS). Unlike traditional high-ratio gearboxes, which amplify motor inertia and reduce efficiency, the MMS distributes torque across multiple motors, allowing for lower gear ratios and less reflected inertia. We developed an optimization model considering motor selection, gear ratios, and gear stages to minimize reflected inertia while meeting load and geometric constraints. A case study on an industrial robot’s shoulder joint demonstrates an 88.84% reduction in reflected inertia using the proposed MMS compared to a conventional single-motor system. The findings suggest that multi-motor systems can significantly reduce reflected inertia, improving back-drivability in robot joints for safer and more efficient pHRI.