Real-time Pose Estimation on Elevation Maps for Wheeled Vehicles

Fast and accurate obstacle detection is a crucial component for autonomous robot navigation. It becomes even more important for a shared control vehicle like an electric wheeled walker, since the safety of the vehicle and the user depend on the correct classification of obstacles. This work describes a method for pose estimation of four-wheeled vehicles, which utilizes the fixed resolution of digital elevation maps to generate a detailed vehicle model. The vehicle's wheels are also approximated using digital elevation maps, allowing efficient calculation of wheel to ground contact points and therefore fast and accurate estimation of valid vehicle poses. To evaluate the proposed method, pose estimates are compared to three datasets including ground truth poses: one created using an external tracking system and two created by simulations of wheeled robots. It is also shown that the method is fast enough for real time operation.