Multi-modal data fusion has gained popularity due to its diverse applications, leading to an
increased demand for external sensor calibration. Despite several proven calibration …

Most sensor setups for onboard autonomous perception are composed of LiDARs and
vision systems, as they provide complementary information that improves the reliability of the …

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 …

The pursuit of autonomous driving relies on developing perception systems capable of
making accurate, robust, and rapid decisions to interpret the driving environment effectively …

3D LiDARs and 2D cameras are increasingly being used alongside each other in sensor
rigs for perception tasks. Before these sensors can be used to gather meaningful data …

The recent trend of fusing complementary data from LiDARs and cameras for more accurate
perception has made the extrinsic calibration between the two sensors critically important …

Effective simulation and testing environment is a vital part in the research of self-driving
vehicles. It is capable of testing self-driving software and hardware quickly in a variety of …

This paper proposes a simple extrinsic calibration method for a multi-sensor system which
consists of six image cameras and a 16-channel 3D LiDAR sensor using a planar …

In rapidly-evolving domains such as autonomous driving the use of multiple sensors with
different modalities is crucial to ensure high operational precision and stability. To correctly …

Calibrating the extrinsic parameters on a system of 3D Light Detection And Ranging (LiDAR)
and the monocular camera is a challenging task, because accurate 3D-2D or 3D-3D point …