Pressure-Bearing Parameter Identification for Martian Soil Based on a Terramechanics Model and Genetic Algorithm

Abstract

A wheel-terrain interaction mechanics model based on terramechanics and simplified force and moment reconstruction is introduced. The model comprises pressure-bearing parameters (combined deformation modulus and slip sinkage exponent), wheel load, driving torque, slip ratio, and wheel sinkage. A genetic algorithm is used to identify the pressure-bearing parameters using a calibration dataset. Experiments were performed on the calibration dataset and a prediction dataset using a single-wheel soil bin to measure the driving torque, wheel sinkage, and drawbar pull of a griddle net wheel under different slip ratios. The proposed model comprises two processes. The first process is to determine the slip sinkage exponent using its empirical value to estimate the combined deformation modulus, and the second is to correct the slip sinkage exponent in which the value of the combined deformation modulus is fixed. The prediction dataset was used to validate the model, with the wheel sinkage and drawbar pull calculated using the wheel-terrain interaction mechanics model with the identified pressure-bearing parameters. The correlation coefficients of the predicted and measured values of the wheel sinkage and drawbar pull were .9712 and .892, respectively. An additional experiment was performed with a continuous slip ratio ranging from .16 to .7 and a wheel load of 5 N to validate the proposed model, and the correlation coefficient between the predicted and measured wheel sinkage was .966. The experimental results demonstrate that the genetic algorithm is able to accurately predict the pressure-bearing parameters, which can be used for traversability prediction, risk assessment, and automatic path planning.