Pose Prediction for Mobile Ground Robots in Uneven Terrain Based on Difference of Heightmaps

Abstract

For traversing uneven terrain in degraded environments, determining the static stability and consequently the tip-over risk of a mobile ground rescue robot is fundamental for planning and evaluation of paths. This paper presents a novel iterative geometric method that reduces the problem of robot pose prediction to two-dimensional image-processing operations by introducing the concept of a robot heightmap. The presented method requires only geometrical and mass information extracted from the widely used unified robot description format (URDF) to compute the robot heightmap, which makes it transferable to a wide range of mobile robot platforms without modification. We demonstrate that the approach accurately predicts the real robot's 6D pose at the input x-y-coordinates. Runtimes allowing the evaluation of poses in the order of ten thousand poses per second show that the method is computationally efficient enough to be used in online path planning.