Learning-based Detection of Leg-Surface Contact using Position Feedback Only.

In this work-in-progress report, we present experimental results of lightweight learning-based leg-contact detection methods for a small hexapod walking robot with position feedback only. The detection of the leg contact with the surface is addressed as anomaly detection using predicted and measured positions of the leg's joints in the leg swing phase. A polynomial regressor and three-layer neural network are evaluated regarding the prediction error and computational requirements using realistic datasets collected with the real hexapod walking robot.