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
Autonomous Multi-Rotor UAVs: A Holistic Approach to Design, Optimization, and Fabrication
Aniruth A, Chirag Satpathy, Jothika K, Nitteesh M, Gokulraj M, Venkatram K, Harshith G, Shristi S, Anushka Vani, Jonathan Spurgeon
AERIAL-CORE: AI-Powered Aerial Robots for Inspection and Maintenance of Electrical Power Infrastructures
Anibal Ollero, Alejandro Suarez, Christos Papaioannidis, Ioannis Pitas, Juan M. Marredo, Viet Duong, Emad Ebeid, Vit Kratky, Martin Saska, Chloe Hanoune, Amr Afifi, Antonio Franchi, Charalampos Vourtsis, Dario Floreano, Goran Vasiljevic, Stjepan Bogdan, Alvaro Caballero, Fabio Ruggiero, Vincenzo Lippiello, Carlos Matilla, Giovanni Cioffi, Davide Scaramuzza, Jose R. Martinez-de-Dios, Begona C. Arrue, Carlos Martin, Krzysztof Zurad, Carlos Gaitan, Jacob Rodriguez, Antonio Munoz, Antidio Viguria
A comprehensive survey of research towards AI-enabled unmanned aerial systems in pre-, active-, and post-wildfire management
Sayed Pedram Haeri Boroujeni, Abolfazl Razi, Sahand Khoshdel, Fatemeh Afghah, Janice L. Coen, Leo ONeill, Peter Z. Fule, Adam Watts, Nick-Marios T. Kokolakis, Kyriakos G. Vamvoudakis
Deep Reinforcement Learning for Joint Cruise Control and Intelligent Data Acquisition in UAVs-Assisted Sensor Networks
Yousef Emami
Drones Guiding Drones: Cooperative Navigation of a Less-Equipped Micro Aerial Vehicle in Cluttered Environments
Václav Pritzl, Matouš Vrba, Yurii Stasinchuk, Vít Krátký, Jiří Horyna, Petr Štěpán, Martin Saska
A Sim-to-Real Deep Learning-based Framework for Autonomous Nano-drone Racing
Lorenzo Lamberti, Elia Cereda, Gabriele Abbate, Lorenzo Bellone, Victor Javier Kartsch Morinigo, Michał Barcis, Agata Barcis, Alessandro Giusti, Francesco Conti, Daniele Palossi
FAPP: Fast and Adaptive Perception and Planning for UAVs in Dynamic Cluttered Environments
Minghao Lu, Xiyu Fan, Han Chen, Peng Lu
TypeFly: Flying Drones with Large Language Model
Guojun Chen, Xiaojing Yu, Neiwen Ling, Lin Zhong
UAV Path Planning for Object Observation with Quality Constraints: A Dynamic Programming Approach
Jiawei Wang, Vincent Chau, Weiwei Wu
Joint User Association, Interference Cancellation and Power Control for Multi-IRS Assisted UAV Communications
Zhaolong Ning, Hao Hu, Xiaojie Wang, Qingqing Wu, Chau Yuen, F. Richard Yu, Yan Zhang