ROSS: Radar Off-road Semantic Segmentation
Peng Jiang Srikanth Saripalli
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.