In this letter, we present a novel method for automatic extrinsic calibration of high-resolution
LiDARs and RGB cameras in targetless environments. Our approach does not require …

This letter proposes an efficient and probabilistic adaptive voxel mapping method for LiDAR
odometry. The map is a collection of voxels; each contains one plane feature that enables …

Global registration is a fundamental task that estimates the relative pose between two
viewpoints of 3D point clouds. However, there are two issues that degrade the performance …

Accurate self and relative state estimation are the critical preconditions for completing swarm
tasks, eg, collaborative autonomous exploration, target tracking, search and rescue. This …

Robotic systems usually evolve on manifolds, which are often overparameterized or
minimally parameterized (but with singularities) in model predictive control (MPC). How to …

In the article, we focus on the robustness of monocular visual-inertial-wheel odometry
(VIWO) in urban environments. In the urban environment, the rapid changes in terrain and …

In this article, we extend the invariant extended Kalman filter (EKF) to light detection and
ranging (LiDAR)-inertial odometry and mapping systems using invariant observer design …

This paper presents a comprehensive forest mapping system using a customized drone
payload equipped with Light Detection and Ranging (LiDAR), cameras, a Global Navigation …

Simultaneous localization and mapping (SLAM) represents a crucial algorithm in the
autonomous navigation of ground vehicles. Several studies were conducted to improve the …

This letter presents a probabilistic voxel-based LiDAR Inertial Odometry framework for
accurate and robust pose estimation. The framework addresses the correspondence …