Unmanned Aerial Vehicle
Unmanned Aerial Vehicles (UAVs), or drones, are increasingly used for diverse applications, driving research focused on improving their autonomy, safety, and efficiency. Current research emphasizes robust navigation and control in complex environments, employing techniques like nonlinear model predictive control and advanced search algorithms for path planning, often coupled with deep learning models (e.g., YOLO, U-Net) for perception and object detection. These advancements are crucial for expanding UAV capabilities in sectors such as agriculture, search and rescue, and infrastructure monitoring, while also addressing critical concerns like security and reliable operation in challenging conditions (e.g., GPS-denied environments, harsh weather).
Papers
Energy-Efficient Techniques for UAVs in Communication-based Applications
Anas Osman, Morteza Alijani
Image Segmentation to Identify Safe Landing Zones for Unmanned Aerial Vehicles
Joe Kinahan, Alan F. Smeaton
Deployment of Aerial Robots after a major fire of an industrial hall with hazardous substances, a report
Hartmut Surmann, Dominik Slomma, Stefan Grobelny, Robert Grafe