ROFeb 17, 2022

Predict the Rover Mobility over Soft Terrain using Articulated Wheeled Bevameter

arXiv:2202.08495v121 citations
Originality Incremental advance
AI Analysis

This addresses mobility challenges for rovers in deformable terrains, offering a practical improvement over existing methods.

The paper tackles the problem of robot mobility failure on soft terrain by proposing an articulated wheeled bevameter that measures contact parameters in real-time to predict wheel slip and sinkage, enabling safer path selection and avoiding dangerous areas like quicksand.

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.

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