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 effectively captures wheel–terrain inter actions 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 is demonstrably effective for our rover equipped with wheel geometries that depart markedly from conventional shapes, suggesting its potential to generalize to arbitrary wheel geometries.