Unmanned Aerial Vehicles

doi:10.3390/books978-3-0365-7825-5

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Unmanned Aerial Vehicles

Edited by

September 2023

426 pages

ISBN978-3-0365-7824-8 (Hardback)
ISBN978-3-0365-7825-5 (PDF)

https://doi.org/10.3390/books978-3-0365-7825-5

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This book is a reprint of the Special Issue Unmanned Aerial Vehicles that was published in

Biology & Life Sciences

Chemistry & Materials Science

Computer Science & Mathematics

Engineering

Environmental & Earth Sciences

Physical Sciences

Summary

Unmanned aerial vehicles (UAVs) are recognized as very useful tools to replace, help, or assist humans in various tasks, such as inspection and monitoring, surveillance, search and rescue, exploration, logistics and transportation, etc. Practical uses for such missions in both civilian and defense contexts have experienced a significant growth as a result of recent technological progresses. Nevertheless, some challenges and open issues regarding ensuring a full operational use of UAVs remain unanswered.

This reprint aims to present recent advances in technologies and algorithms to improve the levels of autonomy, reliability, and safety of UAVs. Different topics are addressed, covering vehicle design and characterization (aerodynamics, flight dynamics, design optimization, communications), algorithms for autonomy (guidance and control, path planning, machine learning, computer vision, perception), traffic and risk management (unmanned traffic management, reliability, risk assessment). Open issues related to new missions such as precision agriculture or telecommunication relays are also considered.

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Hardback

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Keywords

coaxial Tri-rotor MAV; horizontal wind; low-speed wind tunnel; numerical simulation; nonlinear dynamics of flight; bifurcation theory; micro aerial vehicles; strake-wing micro drones; external disturbance; quadrotor; reinforcement learning; UAV; probabilistic maps of impact; ground footprints; Monte Carlo; importance sampling; sensitivity analysis; UTM; system architecture; U-space; UAS; agricultural aviation; UAV; plant protection; review; electrostatic spray technology; droplet deposition; aerial pesticides application; charge to mess ratio; ad hoc networks; experimental study; Flying Ad Hoc Networks; FANET; practical case; routing protocols; testbed; unmanned aerial vehicles; UAV; WiFi; vision-based navigation; cluttered environment; three-dimensional path planner; obstacle avoidance; machine learning; constrained polygonal space; path length; path planning; obstacles; maps; unmanned aerial vehicles; urban environments; time complexity; extremely sparse waypoint graph; object classification; deep learning; convolutional neural network; network architecture; reinforcement learning; UAV; quadrotor; flight control; intelligent control; UAVs; impact time control; sliding mode control; cooperative guidance law; consistency theory; large-scale unmanned aerial vehicle formations; electromagnetic interference; 3 × 3 magic square; chain rules of visual reference; network connectivity; dynamic self-healing capacity; Unmanned Aerial Vehicle (UAV); collision avoidance; safety procedures; reliable architecture; Unified Modeling Language (UML); geofencing; unmanned aircraft systems; UAS traffic management; air traffic control; UAS; low-altitude airspace; computational geometry; path planning; route deconfliction; separation assurance; map processing; hybrid precoding; millimeter wave; non-orthogonal multiple access scheme; massive MIMO; unmanned aerial vehicles; direction of arrivals (DoA); MUSIC algorithm; computer vision; unmanned aerial vehicles; deep transfer learning; object detection; aerial image classification; parameter optimization; fault-tolerant configuration; multirotor UAV; attainable moment set; required moment; UAV; quadcopter; quadplane; multicopter; multirotor; VTOL; tandem-wing; long-range; propeller; propulsion; UAS; dynamometer; thrust; pitch; torque; wind tunnel; n/a