Abstract
In this research paper, we present a novel approach for generating grid maps (elevation maps) from sparse 3D radar point clouds collected from a vehicle. Our approach considers the inherent geometric uncertainty of radar targets, represented by error ellipsoids. A real-time processing pipeline, which has the potential to support applications such as autonomous vehicles and robotics, is developed. Our method shows promising results in capturing rough terrain alterations in an outdoor setting. However, some limitations were observed, including challenges in capturing smaller structures, smooth surfaces, and the presence of artifacts in the generated maps. Future research will focus on addressing these limitations and further enhancing the performance of radar-based topographic mapping. A video, demonstrating the real-time radar-based mapping pipeline in comparison to a lidar-based mapping, is available at https://youtu.be/4Gbd8QKel3U.
Original language | English |
---|---|
Title of host publication | 2023 IEEE International Radar Conference (RADAR) |
Place of Publication | Sydney |
ISBN (Electronic) | 978-1-6654-8278-3 |
DOIs | |
Publication status | Published - 28 Dec 2023 |
Research Field
- Assistive and Autonomous Systems
Keywords
- radar
- real-time mapping
- autonomous navigation
- mobile robotics