Various Fast Moving Drone
Research on fast-moving drones focuses on developing autonomous systems capable of efficient and safe navigation, particularly in complex environments like dense canopies or GPS-denied spaces. Current efforts concentrate on optimizing 3D trajectory planning, employing algorithms like genetic algorithms, graph attention networks, and model predictive control, often coupled with advanced sensor fusion and computer vision techniques for tasks such as object detection, tracking, and mapping. This research is significant for advancing drone capabilities in diverse applications, including agriculture, delivery, infrastructure inspection, and search and rescue, improving efficiency and safety in these domains.
Papers
Deep Reinforcement Learning for Joint Cruise Control and Intelligent Data Acquisition in UAVs-Assisted Sensor Networks
Yousef Emami
Shaping and Being Shaped by Drones: Supporting Perception-Action Loops
Mousa Sondoqah, Fehmi Ben Abdesslem, Kristina Popova, Moira McGregor, Joseph La Delfa, Rachael Garrett, Airi Lampinen, Luca Mottola, Kristina Höök