Steering Performance Optimization for Wheeled Mobile Robots in Granular Media Via DRFM: Enhancing Locomotion Precision and Energy Efficiency

Abstract

Degraded steering performance and increased energy consumption present significant barriers to deploying wheeled mobile robots (WMRs) in granular media such as sand and lunar regolith. This study presents and experimentally validates a systematic optimization framework based on Dynamic Resistive Force Model (DRFM). By integrating the DRFM with a four-wheel vehicle dynamics model featuring front-wheel steering, this approach accurately captures wheel–terrain interactions in granular materials. Subject to a prescribed trajectory root-mean-square error constraint, the framework minimizes energy consumption per unit distance while determining optimal front-wheel steering angles and wheel-speed ratios. Experiments demonstrate that the active steering strategy reduces energy consumption per unit distance by 12.3% while maintaining trajectory root-mean-square error within 6.5%. The proposed method provides a generalizable design paradigm for motion-control optimization on granular terrain, establishing the foundation for long-duration, energy-efficient operations of rovers operating in granular terrain.