Article

Ground Friction Assessment Based on Robot Tire-Ground Interaction

The study drove a skid-steer robot at set speed profiles over five surfaces with different friction characteristics, identifying surface type by the deviation between inertially estimated velocity and wheel odometry velocity. Response delay measurements showed a consistent surface-dependent trend, with the longest delay on soap and the shortest on carpet; spectral features achieved 97.1% balanced classification accuracy under record-level cross-validation. The authors conclude that both the magnitude of velocity mismatch and frequency-domain features contain tire-ground interaction information, which can be used for surface identification and for slip-aware wheel odometry weighting in state estimation.

Part of the event: Robots identify ground friction via wheel-ground velocity mismatch

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