English

ROSS: Radar Off-road Semantic Segmentation

Computer Vision and Pattern Recognition 2023-10-23 v1 Robotics

Abstract

As the demand for autonomous navigation in off-road environments increases, the need for effective solutions to understand these surroundings becomes essential. In this study, we confront the inherent complexities of semantic segmentation in RADAR data for off-road scenarios. We present a novel pipeline that utilizes LIDAR data and an existing annotated off-road LIDAR dataset for generating RADAR labels, in which the RADAR data are represented as images. Validated with real-world datasets, our pragmatic approach underscores the potential of RADAR technology for navigation applications in off-road environments.

Keywords

Cite

@article{arxiv.2310.13551,
  title  = {ROSS: Radar Off-road Semantic Segmentation},
  author = {Peng Jiang and Srikanth Saripalli},
  journal= {arXiv preprint arXiv:2310.13551},
  year   = {2023}
}

Comments

10 pages, 6 figures, accepted by the 18th International Symposium on Experimental Robotics (ISER 2023)

R2 v1 2026-06-28T12:56:55.452Z