Contact Surface Estimation via Haptic Perception
This addresses the challenge of reliable terrain perception for legged robots in adverse conditions where vision fails, though it appears incremental as it builds on haptic sensing approaches.
The paper tackles the problem of estimating terrain geometry and slipperiness for legged robots by proposing an online haptic exploration method, validated in simulation and on a real robot platform.
Legged systems need to optimize contact force in order to maintain contacts. For this, the controller needs to have the knowledge of the surface geometry and how slippery the terrain is. We can use a vision system to realize the terrain, but the accuracy of the vision system degrades in harsh weather, and it cannot visualize the terrain if it is covered with water or grass. Also, the degree of friction cannot be directly visualized. In this paper, we propose an online method to estimate the surface information via haptic exploration. We also introduce a probabilistic criterion to measure the quality of the estimation. The method is validated on both simulation and a real robot platform.