  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.
