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Robots identify ground friction via wheel-ground velocity mismatch
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Kulbhushan Komarraju and co-authors submitted a preprint paper proposing the use of wheel-ground velocity mismatch features from skid-steer robots to identify ground friction characteristics. In the experiments, the robot drove along a set speed profile on five surfaces with different friction characteristics, distinguishing ground types by comparing the deviation between inertia-estimated velocity and wheel odometry velocity; response latency showed a surface-dependent trend, longest on soap and shortest on carpet, and spectral features achieved 97.1% balanced classification accuracy under record-level cross-validation. The authors accordingly conclude that both the magnitude and frequency-domain features of velocity mismatch contain tire-ground interaction information, can be used for ground identification, and can inform slip-aware wheel odometry weighting in state estimation. The paper is an extended abstract, has been submitted to IEEE/ION PLANS 2027, and is under review.
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- 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.
arXiv cs.RO ·