Abstract Accurate camera to LiDAR (Light Detection and Ranging) extrinsic calibration is
important for robotic tasks carrying out tight sensor fusion—such as target tracking and …

This paper presents an open source LiDAR-camera calibration toolbox that is general to
LiDAR and cam-era projection models, requires only one pairing of LiDAR and camera data …

Autonomous driving heavily relies on light detection and ranging (LiDAR) and camera
sensors, which can significantly improve the performance of perception and navigation tasks …

Sensor-based environmental perception is a crucial step for autonomous driving systems,
for which an accurate calibration between multiple sensors plays a critical role. For the …

Reliable real-time extrinsic parameters of 3D Light Detection and Ranging (LiDAR) and
camera are a key component of multi-modal perception systems. However, extrinsic …

Multi-sensor collaborative perception has been a significant trend in self-driving and robot
navigation. The precondition for multi-sensor fusion is the accurate calibration between …

This paper addresses the problem of calibrating extrinsic parameter matrix between an RGB
camera and a LiDAR. Multimodal sensing systems are essential for fully autonomous …

Many approaches for camera and LiDAR calibration are presented in literature but none of
them estimates all intrinsic and extrinsic parameters simultaneously and therefore optimally …

Multi-sensor fusion is for enhancing environment perception and 3D reconstruction in self-
driving and robot navigation. Calibration between sensors is the precondition of effective …

As solid-state LiDAR technology advances, mobile robotics and autonomous driving
increasingly rely on multiple solid-state LiDARs for perception. However, limited or non …