Predict the Rover Mobility over Soft Terrain using Articulated Wheeled Bevameter

TL;DR

This paper introduces an on-board articulated wheeled bevameter system that predicts rover wheel slip and sinkage over soft terrain in real-time, enhancing navigation safety without complex modeling or stochastic methods.

Contribution

It presents a novel bevameter-based mobility prediction method that directly measures contact parameters and predicts wheel behavior, improving accuracy and efficiency over existing approaches.

Findings

Successfully predicts slip and sinkage in real-time

Reduces reliance on complex terramechanics models

Validates approach through multiple experiments

Abstract

Robot mobility is critical for mission success, especially in soft or deformable terrains, where the complex wheel-soil interaction mechanics often leads to excessive wheel slip and sinkage, causing the eventual mission failure. To improve the success rate, online mobility prediction using vision, infrared imaging, or model-based stochastic methods have been used in the literature. This paper proposes an on-board mobility prediction approach using an articulated wheeled bevameter that consists of a force-controlled arm and an instrumented bevameter (with force and vision sensors) as its end-effector. The proposed bevameter, which emulates the traditional terramechanics tests such as pressure-sinkage and shear experiments, can measure contact parameters ahead of the rover's body in real-time, and predict the slip and sinkage of supporting wheels over the probed region. Based on the predicted mobility, the rover can select a safer path in order to avoid dangerous regions such as those covered with quicksand. Compared to the literature, our proposed method can avoid the complicated terramechanics modeling and time-consuming stochastic prediction; it can also mitigate the inaccuracy issues arising in non-contact vision-based methods. We also conduct multiple experiments to validate the proposed approach.