Mobile Ground-Based Radar Sensor for Localization and Mapping: An Evaluation of two Approaches

Abstract

This paper is concerned with robotic applications using a ground-based radar sensor for simultaneous localization and mapping problems. In mobile robotics, radar technology is interesting because of its long range and the robustness of radar waves to atmospheric conditions, making these sensors well-suited for extended outdoor robotic applications. Two localization and mapping approaches using data obtained from a 360° field of view microwave radar sensor are presented and compared. The first method is a trajectory-oriented simultaneous localization and mapping technique, which makes no landmark assumptions and avoids the data association problem. The estimation of the ego-motion makes use of the Fourier-Mellin transform for registering radar images in a sequence, from which the rotation and translation of the sensor motion can be estimated. The second approach uses the consequence of using a rotating range sensor in high speed robotics. In such a situation, movement combinations create distortions in the collected data. Velocimetry is achieved here by explicitly analysing these measurement distortions. As a result, the trajectory of the vehicle and then the radar map of outdoor environments can be obtained. The evaluation of experimental results obtained by the two methods is presented on real-world data from a vehicle moving at 30 km/ h over a 2.5 km course.