04856nam 22011293a 450 991034669210332120250203235434.09783039210312303921031910.3390/books978-3-03921-031-2(CKB)4920000000094748(oapen)https://directory.doabooks.org/handle/20.500.12854/41666(ScCtBLL)43487ea1-ee08-417a-81b7-97e6f158ac21(OCoLC)1117848614(oapen)doab41666(EXLCZ)99492000000009474820250203i20192019 uu engurmn|---annantxtrdacontentcrdamediacrrdacarrierAutonomous Control of Unmanned Aerial VehiclesVictor BecerraMDPI - Multidisciplinary Digital Publishing Institute2019Basel, Switzerland :MDPI,2019.1 electronic resource (270 p.)9783039210305 3039210300 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.History of engineering and technologybicsscsuper twisting sliding mode controller (STSMC)monocular visual SLAMmodulationbio-inspirationsimulationhorizontal controlsensor fusionADRChigh-order sliding modeover-the-horizon air confrontationlongitudinal motion modelautonomous controlreal-time ground vehicle detectionmaneuver decisionnonlinear dynamicsUAV automatic landingharmonic extended state observerimage processingGeneral Visual Inspectionactuator faultsactuator faultremote sensingaerial infrared imageryagricultural UAVSC-FDMtilt rotorsmass eccentricitywind disturbancedecoupling algorithmadaptive discrete meshdisturbancesuper twisting extended state observer (STESO)heuristic explorationsliding mode controlUASQ-NetworkUAV communication systemUAVreinforcement learningautonomous landing area selectionpeak-to-average power ratio (PAPR)slung loadaircraft maintenanceflight mechanicsoctreeunmanned aerial vehicleconvolutional neural networkaircraftperformance evaluationquadrotorvertical take offdata linkpath planningcoaxial-rotorfixed-time extended state observer (FTESO)multi-UAV systemhardware-in-the-loopdistributed swarm controlvertical controlHistory of engineering and technologyBecerra Victor1287664ScCtBLLScCtBLLBOOK9910346692103321Autonomous Control of Unmanned Aerial Vehicles3020273UNINA