  Robust odometry estimation in perceptually degraded environments represents a
key challenge in the field of robotics. In this paper, we propose a LiDAR-radar
fusion method for robust odometry for adverse environment with LiDAR
degeneracy. By comparing the LiDAR point cloud with the radar static point
cloud obtained through preprocessing module, it is possible to identify
instances of LiDAR degeneracy to overcome perceptual limits. We demonstrate the
effectiveness of our method in challenging conditions such as dense smoke,
showcasing its ability to reliably estimate odometry and identify/remove
dynamic points prone to LiDAR degeneracy.
