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
GrADyS-SIM -- A OMNET++/INET simulation framework for Internet of Flying things
Thiago Lamenza, Marcelo Paulon, Breno Perricone, Bruno Olivieri, Markus Endler
Continuously Learning to Detect People on the Fly: A Bio-inspired Visual System for Drones
Ali Safa, Ilja Ocket, André Bourdoux, Hichem Sahli, Francky Catthoor, Georges Gielen
Autonomous UAV for Building Monitoring, Detection and Localisation of Faults
Suhas Thalanki, T Vijay Prashant, Harshith Kumar M B, Shayak Bhadraray, Aravind S, Srikrishna BR, Sameer Dhole
Networking of Internet of UAVs: Challenges and Intelligent Approaches
Peng Yang, Xianbin Cao, Tony Q. S. Quek, Dapeng Oliver Wu