Robust Self-Supervised Extrinsic Self-Calibration
T Kanai, I Vasiljevic, V Guizilini… - 2023 IEEE/RSJ …, 2023 - ieeexplore.ieee.org
Autonomous vehicles and robots need to operate over a wide variety of scenarios in order to
complete tasks efficiently and safely. Multi-camera self-supervised monocular depth …
complete tasks efficiently and safely. Multi-camera self-supervised monocular depth …
SceneCalib: Automatic targetless calibration of cameras and LiDARs in autonomous driving
A Sen, G Pan, A Mitrokhin… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
Accurate camera-to-lidar calibration is a requirement for sensor data fusion in many 3D
perception tasks. In this paper, we present SceneCalib, a novel method for simultaneous self …
perception tasks. In this paper, we present SceneCalib, a novel method for simultaneous self …
[HTML][HTML] A novel and simplified extrinsic calibration of 2D laser rangefinder and depth camera
W Zhou, H Chen, Z Jin, Q Zuo, Y Xu, K He - Machines, 2022 - mdpi.com
It is too difficult to directly obtain the correspondence features between the two-dimensional
(2D) laser-range-finder (LRF) scan point and camera depth point cloud, which leads to a …
(2D) laser-range-finder (LRF) scan point and camera depth point cloud, which leads to a …
Quantifying Uncertainties along the Automated Driving Stack
S Peters, J Peters, R Findeisen - ATZ worldwide, 2023 - Springer
To adequately consider the risks of a behavior in the planning and control of automated
driving maneuvers, professors at TU Darmstadt propose the consistent propagation of …
driving maneuvers, professors at TU Darmstadt propose the consistent propagation of …