Journal Article
3D-3D Self-Calibration of Sensors Using Point Cloud Data
2021-04-06
2021-01-0086
Self-calibration of sensors has become highly essential in the era of self-driving cars. Reducing the sensors’ errors increases the reliability of the decisions made by the autonomous systems. Various methods are currently under investigation but the traditional methods still prevail which maintain a strong dependency on human experts and expensive equipment that consume significant amounts of labor and time. Recently, various calibration techniques proposed for extrinsic calibration for Autonomous Vehicles (AVs) mostly rely on the camera 2D images and depth map to calibrate the 3D LiDAR points. While most methods work with the whole frame, some methods use the objects in the frame to perform the calibration. To the best of our knowledge, majority of these self-calibration methods rely on using actual or falsified ground truth values.