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Wheel Vision: Wheel-Terrain Interaction Measurement and Analysis Using a Sensorized Transparent Wheel on Deformable Terrains

Feng Xue, Wang Zheng-yin, Ye Yuan, Zheng Zhu, Liang Ding, Zhenzhong Jia

Year
2023
Citations
15

Abstract

The off-road locomotion of wheeled mobile robots (WMRs) over soft terrains can be quite challenging due to the complicated wheel-terrain interaction (WTI). To avoid unforeseen non-geometric hazards such as excessive sinkage or slippage, it is crucial to oversee these terrain-related uncertainties. However, determining the appropriate sensing principle for WTI and hazard prediction remains an open problem. This letter showcases an onboard sensorized transparent wheel concept (STW) aiming to explicitly characterize the WTI over deformable terrains for rovers. The STW configuration can provide directly in-wheel interaction views, thereby offering in-wheel measurement (IM) of WTI parameters and observations of soil flow simultaneously. Unlike traditional vision-based methods, this in-situ wheel vision can characterize the entire contact geometry distributions, eliminating complicated yet inaccurate model-based stochastic estimations. Consequently, it can achieve robust and real-time (30 Hz) performance even under complex motions. We conduct representative terrain experiments on a single-wheel testbed to verify the performance of our proposed STW system, and showcase its applicability as a terramechanics test tool to remodel WTI mechanics, as seen in <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://youtu.be/aYKW1Pp4ENw</uri> .

Keywords

TerrainTestbedComputer scienceArtificial intelligenceSlippageRoboticsComputer visionSimulationRobotEngineering

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