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 - Page 5
NavAgent: Multi-scale Urban Street View Fusion For UAV Embodied Vision-and-Language Navigation
Youzhi Liu, Fanglong Yao, Yuanchang Yue, Guangluan Xu, Xian Sun, Kun FuBiomass phenotyping of oilseed rape through UAV multi-view oblique imaging with 3DGS and SAM model
Yutao Shen (1 and 2), Hongyu Zhou (3), Xin Yang (1 and 2), Xuqi Lu (1 and 2), Ziyue Guo (1 and 2), Lixi Jiang (3), Yong He (1 and 2)+10DNN Task Assignment in UAV Networks: A Generative AI Enhanced Multi-Agent Reinforcement Learning Approach
Xin Tang, Qian Chen, Wenjie Weng, Binhan Liao, Jiacheng Wang, Xianbin Cao, Xiaohuan Li
BuckTales : A multi-UAV dataset for multi-object tracking and re-identification of wild antelopes
Hemal Naik, Junran Yang, Dipin Das, Margaret C Crofoot, Akanksha Rathore, Vivek Hari SridharFlight Time Improvement Using Adaptive Model Predictive Control for Unmanned Aerial Vehicles
Huy-Hoang Ngo, Thanh Nguyen Canh, Xiem HoangVan
Reshaping UAV-Enabled Communications with Omnidirectional Multi-Rotor Aerial Vehicles
Daniel Bonilla Licea, Giuseppe Silano, Hajar El Hammouti, Mounir Ghogho, Martin SaskaToward Integrating Semantic-aware Path Planning and Reliable Localization for UAV Operations
Thanh Nguyen Canh, Huy-Hoang Ngo, Xiem HoangVan, Nak Young Chong
Drone Acoustic Analysis for Predicting Psychoacoustic Annoyance via Artificial Neural Networks
Andrea Vaiuso, Marcello Righi, Oier Coretti, Moreno ApicellaA Time and Place to Land: Online Learning-Based Distributed MPC for Multirotor Landing on Surface Vessel in Waves
Jess Stephenson, William S. Stewart, Melissa Greeff