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Tactile sensing on human feet is crucial for motion control, however, has notbeen explored in robotic counterparts. This work is dedicated to endowingtactile sensing to legged robot's feet and showing that a single-legged robotcan be stabilized with only tactile sensing signals from its foot. We propose arobot leg with a novel vision-based tactile sensing foot system and implement aprocessing algorithm to extract contact information for feedback control instabilizing tasks. A pipeline to convert images of the foot skin intohigh-level contact information using a deep learning framework is presented.The leg was quantitatively evaluated in a stabilization task on a tiltingsurface to show that the tactile foot was able to estimate both the surfacetilting angle and the foot poses. Feasibility and effectiveness of the tactilesystem were investigated qualitatively in comparison with conventionalsingle-legged robotic systems using inertia measurement units (IMU).Experiments demonstrate the capability of vision-based tactile sensors inassisting legged robots to maintain stability on unknown terrains and thepotential for regulating more complex motions for humanoid robots.

A Tactile Sensing Foot for Single Robot Leg Stabilization