Far-range perception is essential for intelligent transportation systems. The main challenge
of far-range perception is due to the difficulty of performing accurate object detection and …

The rapid development of augmented reality (AR), 3D reconstruction, simultaneous
localization and mapping (SLAM), and autonomous driving requires off-the-shelf camera …

Multimodal perception represents a vital approach for observing non-cooperative targets in
space. The accurate determination of the extrinsic parameters for monocular camera and …

Robust and reliable calibration forms the foundation of efficient multi-sensor fusion. Most
existing calibration methods are offline and rely on artificial targets, which is time consuming …

This paper proposes a novel camera–LiDAR calibration method that utilizes an iterative
random sampling and intersection line-based quality evaluation using a foldable plane pair …

Precise and robust extrinsic parameter calibration is fundamental for LiDAR-camera multi-
modal sensing applications. However, most existing methods assume that sensors have the …

LiDAR-camera extrinsic calibration (LCEC) is crucial for data fusion in intelligent vehicles.
Offline, target-based approaches have long been the preferred choice in this field. However …

This article proposes a novel method for extrinsic calibration between LiDAR and camera
sensors given a single observation of one calibration target board. Particularly, to improve …

Purpose In the context of fire incidents within buildings, efficient scene perception by
firefighting robots is particularly crucial. Although individual sensors can provide specific …

Notation conventions for rigid transformations are as diverse as they are fundamental to the
field of robotics. A well-defined convention that is practical, consistent and unambiguous is …