Steering Performance Optimization for Wheeled Mobile Robots in Granular Media Via DRFM: Enhancing Locomotion Precision and Energy Efficiency
Chuang Cao, Lei Huang, Feiyu Zhang, YH Yin
AI summary
Problem
Wheeled mobile robots suffer from degraded steering precision and high energy consumption in granular media due to unpredictable wheel-terrain interactions that invalidate traditional non-holonomic steering models.
Approach
The authors couple a Dynamic Resistive Force Model with a four-wheel dynamics model to simulate wheel-soil interactions, then apply a Sobol sequence-based parameter sweep to optimize steering angles and wheel-speed ratios under a trajectory accuracy constraint.
Key results
- 12.3% reduction in energy consumption per unit distance
- 6.5% average normalized trajectory RMS error maintained across turning radii
- Computationally efficient DRFM simulation enabling rapid parameter sweeps
- Experimental validation on a custom rover with non-conventional spiral-lugged wheels
Why it matters
Provides a scalable optimization method for improving rover efficiency and navigation accuracy in planetary exploration and hazardous terrain applications.
Abstract
Degraded steering performance and increased en- ergy consumption present significant barriers to deploying wheeled mobile robots (WMRs) in granular media such as sand and lunar regolith. This study presents and experimen- tally validates a systematic optimization framework based on the Dynamic Resistive Force Model (DRFM). By integrating the DRFM with a four-wheel vehicle dynamics model fea- turing front-wheel steering, this approach effectively 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 an average normalized trajectory root-mean-square error of 6.5% across the tested turning radii. 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.