Real-Time Modeling of Environmental Forces During Pushing in Granular Media Using S-RFT
Jiaxin Liu, Yang Tian, Longchuan Li, Shugen Ma, Zhongkui Wang
AI summary
Problem
Most existing resistive force models fail to explicitly account for motion-induced terrain deformation under varying velocity directions, limiting accurate real-time force prediction for robots pushing through granular media.
Approach
The authors generalize the shallow resistive force theory (S-RFT) to embed motion-induced terrain deformation effects into force predictions, validating the framework through discrete element simulations and single-lug wheel experiments across varying velocity directions.
Key results
- S-RFT accurately captures force responses across varying velocity directions in translational pushing motions
- The model outperforms conventional RFT by accounting for subsurface compaction and surface pile formation
- S-RFT successfully predicts environmental forces during single-lug rotational motion in granular media
- DEM simulations and experiments confirm that terrain deformation dominates force asymmetry during lug insertion and withdrawal
Why it matters
This work enables more accurate real-time force prediction for robots navigating deformable terrains, directly benefiting the design and control of planetary rovers and sand-traversing robotic systems.
Abstract
Modeling environmental forces remains a critical challenge in the design and control of robots operating on granular terrain. In pushing locomotion, propulsion is gener- ated by displacing a large number of particles; however, the resulting terrain deformation complicates accurate real-time force prediction. Most existing resistive force models do not explicitly account for these deformation effects. To address this limitation, we develop a force model that incorporates motion-induced terrain deformation for pushing motions in granular media. A wheel lug is adopted as a representa- tive element. We first investigate translational motion using the discrete element method (DEM) to characterize terrain deformation under different velocity directions. The analysis identifies dominant deformation patterns, which are embedded in the force model. Building on this analysis, we examine the rotational motion of a single lug through experiments, DEM simulations, and model predictions. The results demonstrate that the proposed model accurately captures force responses across varying velocity directions, exhibiting closer agreement with DEM and experiments than conventional approaches. This work advances real-time force modeling for robot-granular terrain interactions and highlights the potential of deformation- integrated models in deformable environments.