Accurate Rover Mobility Analysis Using HILS-DRFT with Real-Time Parameter Tuning Approach

EasyChair Preprint 15194

Abstract

Offroad mobility of extraterrestrial exploration rovers can be significantly degraded by vehicle slippage on soft terrain covered with fine powdery sand known as regolith. Comprehensive design analysis and verification of the rover’s mobility have been widely investigated using numerical and experimental approaches. Numerical simulations for the mobility analysis require accurate modeling of the contact forces between the wheel and sand. While several wheel-sand interaction models have been proposed based on the Bekker-Wong-Reece theory, the Dynamic Resistive Force Theory (DRFT) proposed in the early 2020s is a notable approach for its low computational cost and adaptability to high-speed motion. The scaling factor used in DRFT is the only parameter for representing soil-dependent parameters, and its value needs to be empirically tuned to achieve accurate and reliable mobility analysis. Therefore, the authors have integrated a single-wheel test bed into a closed-loop Hardware-In-the-Loop Simulation (HILS) associated with DRFT. This HILS-DRFT experimentally observes the characteristics of the wheel sinking phenomenon in the wheel test bed, and then, the value of the scaling factor is tuned in real-time based on the difference between the observed wheel sinkage and the DRFT simulation. This real-time parameter tuning method accurately reproduces wheel mobility, particularly in its transient states, which were previously unachievable with DRFT alone. The proposed HILS-DRFT with the real-time tuning method will contribute to the efficient and reliable development of rovers.

Keyphrases: Resistive Force Theory, Terramechanics, hardware-in-the-loop simulation

@booklet{EasyChair:15194,
  author    = {Takahiro Fuke and Sora Ishikawa and Genya Ishigami},
  title     = {Accurate Rover Mobility Analysis Using HILS-DRFT with Real-Time Parameter Tuning Approach},
  howpublished = {EasyChair Preprint 15194},
  year      = {EasyChair, 2024}}