On the pursuit of autonomous flying robots, the scientific community has been developing
onboard real-time algorithms for localisation, mapping and planning. Despite recent …

The ability of drones to access disaster areas has been proven powerful and flexible for
acquiring first-hand optical imagery data for environmental observation. However, such …

This paper addresses real-time dense 3D reconstruction for a resource-constrained
Autonomous Underwater Vehicle (AUV). Underwater vision-guided operations are among …

Unmanned aerial vehicles (UAVs) can capture high-quality aerial photos and have been
widely used for large-scale urban 3D reconstruction. However, even with the help of …

Existing laser-based 2D simultaneous localization and mapping (SLAM) methods exhibit
limitations with regard to either efficiency or map representation. An ideal method should …

In this work, we develop a new surface reconstruction pipeline that combines monocular
camera images and LiDAR measurements from a moving sensor rig to reconstruct dense 3D …

This article presents a novel framework for acquiring visual data around 3D infrastructures,
by establishing a team of fully autonomous Micro Aerial Vehicles (MAVs) with robust …

Simultaneous localization and mapping (SLAM) is a major challenge in the field of robotics.
Existing literature reviews are classified according to the localization technology or sensors …

This work presents an online learning-based control method for improved trajectory tracking
of unmanned aerial vehicles using both deep learning and expert knowledge. The proposed …

This paper presents AeroTraj, a system that enables fast, accurate, and automated
reconstruction of 3D models of large buildings using a drone-mounted LiDAR. LiDAR point …