Faster LiDAR Based on Predictive Deep Learning Model

Normal LiDAR in the market runs at 10hz, which is sufficient for state-of-the-art autonomous road vehicle, but not enough for autonomous racing vehicle that runs at 180mph. In order to make a "faster LiDAR", inspired by the fact that camera(30+hz) and LiDAR(10hz) holds different operating frequency, we propose a method that uses both camera and LiDAR history information to predict future LiDAR frames.

Replication of the “PointPainting”

By replicating the state-of-the-art sensor fusion detection model ["PointPainting"](, we further use this tool to test/evaluate our 3D point cloud predictive model and end-to-end extrinsic sensor calibration model.