TL;DR
This is the first work that is able to recover the pose of an UAV at this scale and rate of convergence, while allowing significant seasonal difference between camera observations and map.
The paper proposes a method for visual positioning of unmanned aerial vehicles (UAVs) based on descriptor-based computer vision algorithms. The use of optical navigation is investigated as an auxiliary mechanism under conditions of degradation or total absence of global navigation satellite system (GNSS) signals, where...
Quadrotor unmanned aerial vehicles (UAVs) have advantages such as simple structure, flexible manipulation, and strong capabilities of vertical takeoff/landing and hovering, thus being widely applied in various complex environments and tasks. However, their short endurance limits the scope of application. The collaborat...
Autonomous navigation of multi-rotor Unmanned Aerial Vehicles (UAVs) in complex low-altitude environments remains challenging due to severe onboard computational constraints, sensor blind spots, and unpredictable dynamic obstacles. This paper presents a lightweight, integrated autonomous obstacle avoidance system for q...
Autonomous landings of uncrewed aerial vehicles (UAV) on moving ground vehicles remains a challenging issue, since the reliability of onboard sensors varies during flights. Camera vision measurements may be blurred by motion, partially obscure the target, and be distorted by changes in light. LiDAR height measurements...
The development of intelligent unmanned aerial vehicles with onboard computer vision capabilities is increasingly relevant to search and rescue operations. However, real-time human detection on compact UAV platforms remains challenging due to limited computational resources, varying environmental conditions, and the sm...
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