Surface Shape Identification with Legged Robots Using Tactile Sensing

This paper presents an approach to terrain shape detection using an array of tactile sensors or motor torque and encoders. A sparse point cloud at points where the surface is touched by the robot’s feet is converted into a polygonal mesh and a dense 3D point cloud using $\alpha$-shapes derived from a 2D Delaunay triangulation. Cloud-to-Cloud (C2C) and Cloud-to-Mesh (C2M) metrics are used to validate the solution. In the study, a mathematical model of the robot-surface system is developed and numerical experiments are performed on the basis of this model. A modification of Delaunay triangulation is proposed to account for impassable or unexplored areas of the surface. The results of mathematical modeling are confirmed in hardware experiments.