Reprint

Autonomous Control of Unmanned Aerial Vehicles

Edited by
June 2019
270 pages
  • ISBN978-3-03921-030-5 (Paperback)
  • ISBN978-3-03921-031-2 (PDF)

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

Computer Science & Mathematics
Engineering
Physical Sciences
Summary

Unmanned aerial vehicles (UAVs) are being increasingly used in different applications in both military and civilian domains. These applications include surveillance, reconnaissance, remote sensing, target acquisition, border patrol, infrastructure monitoring, aerial imaging, industrial inspection, and emergency medical aid. Vehicles that can be considered autonomous must be able to make decisions and react to events without direct intervention by humans. Although some UAVs are able to perform increasingly complex autonomous manoeuvres, most UAVs are not fully autonomous; instead, they are mostly operated remotely by humans. To make UAVs fully autonomous, many technological and algorithmic developments are still required. For instance, UAVs will need to improve their sensing of obstacles and subsequent avoidance. This becomes particularly important as autonomous UAVs start to operate in civilian airspaces that are occupied by other aircraft. The aim of this volume is to bring together the work of leading researchers and practitioners in the field of unmanned aerial vehicles with a common interest in their autonomy. The contributions that are part of this volume present key challenges associated with the autonomous control of unmanned aerial vehicles, and propose solution methodologies to address such challenges, analyse the proposed methodologies, and evaluate their performance.

Format
  • Paperback
License
© 2019 by the authors; CC BY-NC-ND license
Keywords
UAV automatic landing; monocular visual SLAM; autonomous landing area selection; aerial infrared imagery; real-time ground vehicle detection; convolutional neural network; unmanned aerial vehicle; quadrotor; slung load; disturbance; harmonic extended state observer; quadrotor; super twisting extended state observer (STESO); super twisting sliding mode controller (STSMC); wind disturbance; actuator faults; agricultural UAV; multi-UAV system; distributed swarm control; performance evaluation; remote sensing; over-the-horizon air confrontation; maneuver decision; Q-Network; heuristic exploration; reinforcement learning; UAV communication system; data link; SC-FDM; peak-to-average power ratio (PAPR); modulation; quadrotor; ADRC; fixed-time extended state observer (FTESO); high-order sliding mode; wind disturbance; actuator fault; mass eccentricity; UAS; aircraft maintenance; General Visual Inspection; sensor fusion; image processing; flight mechanics; coaxial-rotor; UAV; aircraft; longitudinal motion model; decoupling algorithm; sliding mode control; UAV; bio-inspiration; autonomous control; horizontal control; vertical control; tilt rotors; nonlinear dynamics; simulation; hardware-in-the-loop; vertical take off; UAV; path planning; adaptive discrete mesh; octree; n/a