For environmental perception, autonomous vehicles and intelligent roadside infrastructure
systems contain multiple sensors, that is, radio detection and ranging (radar), light detection …

The combination of light detection and rangings (LiDARs) and cameras enables a mobile
robot to perceive environments with multimodal data, becoming a key factor in achieving …

Multi-modal sensing often involves determining correspondences between each domain's
signals, which in turn depends on the accurate extrinsic calibration of the sensors …

With the rapid development of autonomous driving, robotics, and intelligent transportation,
multi-sensor-based environment sensing technology for intelligent vehicles has become a …

In intelligent driving systems, the multisensor fusion perception system comprising multiple
cameras and LiDAR has become a crucial component. It is essential to have stable extrinsic …

This paper introduces a novel targetless method for joint intrinsic and extrinsic calibration of
LiDAR-camera systems using plane-constrained bundle adjustment (BA). Our method …

Current traditional methods for LiDAR-camera extrinsics estimation depend on offline targets
and human efforts, while learning-based approaches resort to iterative refinement for …

Autonomous vehicles are equipped with a multi-modal sensor setup to enable the car to
drive safely. The initial calibration of such perception sensors is a highly matured topic and …

The extrinsic transformation between LiDAR and camera is 6-DoF, but the motion of robot is
mainly 3-DoF. The classical hand–eye calibration method used in unmanned aerial vehicles …

Accurate calibration of LiDAR and camera in targetless environments is a crucial task in
various applications. This paper proposes an automatic and efficient calibration method for …