Faster Collision Checks for Car-Like Robot Motion Planning

Abstract

In this paper, we describe how collision checking for car-like robots can be sped up utilizing system knowledge. Their non-holonomic motion, while being a challenge for motion planning, is utilized here to place discs which are used as an approximation of the robot's shape in a predictive manner. For ease of comparison, we assume the robot to be rectangular, i. e., we use bounding boxes. Our algorithm is compared to a widely-used baseline and shows similar performance in terms of under- and oversampling while being approximately 20-40 % faster. Another feature of the algorithm is its predictive nature: with the frontal disc, we already check for collisions that would occur with the rear disc in the next sample, assuming near-constant curvature. While this might be conservative in some cases where large steering rates are necessary, in our evaluation even tight corridors could be navigated without negative effects.