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固定翼无人机在线航迹规划方法 Title:OnlineTrajectoryPlanningMethodsforFixed-WingUnmannedAerialVehicles Abstract: Inrecentyears,fixed-wingunmannedaerialvehicles(UAVs)havegainedsignificantpopularityduetotheirextensiveapplicationsinvariousfields,suchasagriculture,surveillance,andaerialmapping.OneofthekeychallengesinthesuccessfuldeploymentofUAVsisthedevelopmentofefficientandreliableonlinetrajectoryplanningmethods.Thispaperprovidesanin-depthanalysisofexistingapproachesforonlinetrajectoryplanningforfixed-wingUAVs,highlightingtheiradvantages,limitations,andpotentialfutureimprovements.Theaimistoprovideacomprehensiveunderstandingofthecurrentstate-of-the-arttechniquesfortrajectoryplanninginordertoenhancethecapabilitiesandperformanceoffixed-wingUAVsinreal-timeoperations. 1.Introduction 1.1Background 1.2ProblemStatement 1.3Objective 2.Fixed-WingUAVFlightDynamics 2.1BasicFlightDynamics 2.2ConstraintsandLimitations 3.OnlineTrajectoryPlanningTechniques 3.1Grid-BasedApproaches 3.2Sampling-BasedApproaches 3.3Optimization-BasedApproaches 3.4MachineLearning-BasedApproaches 3.5HybridApproaches 4.EvaluationMetrics 4.1Safety 4.2Efficiency 4.3MissionSuitability 5.ComparisonofExistingMethods 5.1Grid-BasedApproaches:ProsandCons 5.2Sampling-BasedApproaches:ProsandCons 5.3Optimization-BasedApproaches:ProsandCons 5.4MachineLearning-BasedApproaches:ProsandCons 5.5HybridApproaches:ProsandCons 6.ChallengesandLimitations 6.1Real-TimeComputation 6.2ComputationalComplexity 6.3EnvironmentalFactors 6.4AlgorithmRobustness 7.FutureDirectionsandPotentialImprovements 7.1IntegrationofReal-TimeData 7.2AdvancedOptimizationTechniques 7.3EnhancedMachineLearningModels 7.4ImprovedPathSmoothingAlgorithms 8.CaseStudiesandApplications 8.1SearchandRescueOperations 8.2PrecisionAgriculture 8.3AerialMappingandSurveying 9.Conclusion 9.1SummaryofFindings 9.2RecommendationsforFutureResearch Theproposedpaperaimstopresentacomprehensiveoverviewofonlinetrajectoryplanningmethodsforfixed-wingUAVs.Itwilldelveintothefundamentalconceptsoffixed-w