Predict the Rover Mobility Over Soft Terrain Using Articulated Wheeled Bevameter

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 rover performance, online mobility prediction using vision, infrared imaging, or model-based stochastic methods have been used in the literature. This letter 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 the contact parameters ahead of the rover's body in real-time, and predict the slip and sinkage of the subsequent supporting wheels over the probed region. Based on the mobility prediction, the rover can select a proper path in order to avoid hazardous regions such as those covered with loose sand. Compared to the literature, our proposed method can avoid the complicated yet inaccurate vehicle-terrain interaction 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 and the applicability of the articulated bevameter as an on-board equipment to study wheel-terrain interaction mechanics.

Topics & Concepts