Autonomous Control of Unmanned Aerial Vehicles

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, a...

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Հիմնական հեղինակ: Becerra, Victor
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Հրապարակվել է: MDPI - Multidisciplinary Digital Publishing Institute 2021
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author Becerra, Victor
author_browse Becerra, Victor
author_facet Becerra, Victor
author_sort Becerra, Victor
collection Directory of Open Access Books
description 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.
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language eng
publishDate 2021
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spelling doab-20.500.12854ir-416662024-04-11T15:10:41Z Autonomous Control of Unmanned Aerial Vehicles Becerra, Victor TA1-2040 T1-995 n/a super twisting sliding mode controller (STSMC) monocular visual SLAM modulation bio-inspiration simulation horizontal control sensor fusion ADRC high-order sliding mode over-the-horizon air confrontation longitudinal motion model autonomous control real-time ground vehicle detection maneuver decision nonlinear dynamics UAV automatic landing harmonic extended state observer image processing General Visual Inspection actuator faults actuator fault remote sensing aerial infrared imagery agricultural UAV SC-FDM tilt rotors mass eccentricity wind disturbance decoupling algorithm adaptive discrete mesh disturbance super twisting extended state observer (STESO) heuristic exploration sliding mode control UAS Q-Network UAV communication system UAV reinforcement learning autonomous landing area selection peak-to-average power ratio (PAPR) slung load aircraft maintenance flight mechanics octree unmanned aerial vehicle convolutional neural network aircraft performance evaluation quadrotor vertical take off data link path planning coaxial-rotor fixed-time extended state observer (FTESO) multi-UAV system hardware-in-the-loop distributed swarm control vertical control thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology 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. 2021-02-11T08:44:45Z 2021-02-11T08:44:45Z 2019-06-26 08:44:06 2019 book 33707 9783039210305 9783039210312 https://directory.doabooks.org/handle/20.500.12854/41666 eng image/jpeg Attribution-NonCommercial-NoDerivatives 4.0 International https://mdpi.com/books/pdfview/book/1377 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-03921-031-2 10.3390/books978-3-03921-031-2 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783039210305 9783039210312 270 open access
spellingShingle TA1-2040
T1-995
n/a
super twisting sliding mode controller (STSMC)
monocular visual SLAM
modulation
bio-inspiration
simulation
horizontal control
sensor fusion
ADRC
high-order sliding mode
over-the-horizon air confrontation
longitudinal motion model
autonomous control
real-time ground vehicle detection
maneuver decision
nonlinear dynamics
UAV automatic landing
harmonic extended state observer
image processing
General Visual Inspection
actuator faults
actuator fault
remote sensing
aerial infrared imagery
agricultural UAV
SC-FDM
tilt rotors
mass eccentricity
wind disturbance
decoupling algorithm
adaptive discrete mesh
disturbance
super twisting extended state observer (STESO)
heuristic exploration
sliding mode control
UAS
Q-Network
UAV communication system
UAV
reinforcement learning
autonomous landing area selection
peak-to-average power ratio (PAPR)
slung load
aircraft maintenance
flight mechanics
octree
unmanned aerial vehicle
convolutional neural network
aircraft
performance evaluation
quadrotor
vertical take off
data link
path planning
coaxial-rotor
fixed-time extended state observer (FTESO)
multi-UAV system
hardware-in-the-loop
distributed swarm control
vertical control
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
Becerra, Victor
Autonomous Control of Unmanned Aerial Vehicles
title Autonomous Control of Unmanned Aerial Vehicles
title_full Autonomous Control of Unmanned Aerial Vehicles
title_fullStr Autonomous Control of Unmanned Aerial Vehicles
title_full_unstemmed Autonomous Control of Unmanned Aerial Vehicles
title_short Autonomous Control of Unmanned Aerial Vehicles
title_sort autonomous control of unmanned aerial vehicles
topic TA1-2040
T1-995
n/a
super twisting sliding mode controller (STSMC)
monocular visual SLAM
modulation
bio-inspiration
simulation
horizontal control
sensor fusion
ADRC
high-order sliding mode
over-the-horizon air confrontation
longitudinal motion model
autonomous control
real-time ground vehicle detection
maneuver decision
nonlinear dynamics
UAV automatic landing
harmonic extended state observer
image processing
General Visual Inspection
actuator faults
actuator fault
remote sensing
aerial infrared imagery
agricultural UAV
SC-FDM
tilt rotors
mass eccentricity
wind disturbance
decoupling algorithm
adaptive discrete mesh
disturbance
super twisting extended state observer (STESO)
heuristic exploration
sliding mode control
UAS
Q-Network
UAV communication system
UAV
reinforcement learning
autonomous landing area selection
peak-to-average power ratio (PAPR)
slung load
aircraft maintenance
flight mechanics
octree
unmanned aerial vehicle
convolutional neural network
aircraft
performance evaluation
quadrotor
vertical take off
data link
path planning
coaxial-rotor
fixed-time extended state observer (FTESO)
multi-UAV system
hardware-in-the-loop
distributed swarm control
vertical control
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
topic_facet TA1-2040
T1-995
n/a
super twisting sliding mode controller (STSMC)
monocular visual SLAM
modulation
bio-inspiration
simulation
horizontal control
sensor fusion
ADRC
high-order sliding mode
over-the-horizon air confrontation
longitudinal motion model
autonomous control
real-time ground vehicle detection
maneuver decision
nonlinear dynamics
UAV automatic landing
harmonic extended state observer
image processing
General Visual Inspection
actuator faults
actuator fault
remote sensing
aerial infrared imagery
agricultural UAV
SC-FDM
tilt rotors
mass eccentricity
wind disturbance
decoupling algorithm
adaptive discrete mesh
disturbance
super twisting extended state observer (STESO)
heuristic exploration
sliding mode control
UAS
Q-Network
UAV communication system
UAV
reinforcement learning
autonomous landing area selection
peak-to-average power ratio (PAPR)
slung load
aircraft maintenance
flight mechanics
octree
unmanned aerial vehicle
convolutional neural network
aircraft
performance evaluation
quadrotor
vertical take off
data link
path planning
coaxial-rotor
fixed-time extended state observer (FTESO)
multi-UAV system
hardware-in-the-loop
distributed swarm control
vertical control
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
url 33707
work_keys_str_mv AT becerravictor autonomouscontrolofunmannedaerialvehicles