Odometry is crucial for robot navigation, particularly in situations where global positioning
methods like global positioning system are unavailable. The main goal of odometry is to …

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 …

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 …

Conventional sensor-based localization relies on high-precision maps, which are generally
built using specialized mapping techniques involving high labor and computational costs. In …

Simultaneous determination of sensor poses and scene geometry is a fundamental problem
for robot vision that is often achieved by Bundle Adjustment (BA). This article presents an …

Place recognition is crucial for robot localization and loop closure in simultaneous
localization and mapping (SLAM). Light Detection and Ranging (LiDAR), known for its …

Current multi-modal object detection approaches focus on the vehicle domain and are
limited in the perception range and the processing capabilities. Roadside sensor units …

Accurate and long-distance depth estimation for visual landmarks is challenging in visual-
inertial navigation systems (VINSs). In visual-degenerated scenes with illumination changes …

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 …

Accurate intersensor spatiotemporal transformation is the fundamental prerequisite for
multisensor fusion. However, traditional discrete-time calibration methods have natural …