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基于改进RRT-Connect的无人机航迹规划算法.docx

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基于改进RRT-Connect的无人机航迹规划算法 Title:ImprovedRRT-ConnectAlgorithmforUnmannedAerialVehicleTrajectoryPlanning Abstract: UnmannedAerialVehicles(UAVs)havegainedsignificantpopularityduetotheirapplicationinvariousfieldssuchassurveillance,reconnaissance,anddeliveryservices.OneofthecriticalchallengesinUAVoperationsisefficientandsafetrajectoryplanning.TheRapidly-exploringRandomTree(RRT)algorithmhasproventobeaneffectiveapproachforsolvingmotionplanningproblems.However,theoriginalRRTalgorithmoftensuffersfromslowconvergenceandinefficientexploration.ThispaperproposesanimprovedRRT-ConnectalgorithmthataddressestheselimitationsandprovidesamoreefficienttrajectoryplanningsolutionforUAVs. Introduction: UAVtrajectoryplanninginvolvesdeterminingasafeandoptimalpathfortheUAVtonavigatefromitscurrentlocationtoadesiredtargetwhileavoidingobstaclesandconsideringdynamicconstraints.Theplanningshouldaimtominimizecollisionrisk,energyconsumption,andoverallmissiontime.TheRRTalgorithmiswidelyusedduetoitsabilitytohandlehigh-dimensionalconfigurationspaces,butitisnotspecificallydesignedforUAVapplications.Therefore,enhancementsareneededtoadaptthealgorithmtobettersuittherequirementsofUAVtrajectoryplanning. ImprovedRRT-ConnectAlgorithm: TheproposedimprovedRRT-ConnectalgorithmincorporatesseveralmodificationstoenhancetheperformanceoftheoriginalRRTalgorithm.Thesemodificationsinclude: 1.Goal-directedexploration:IntheoriginalRRTalgorithm,randomsamplesaregenerateduniformlyintheconfigurationspace.However,forUAVtrajectoryplanning,itismoreeffectivetobiasthesamplingtowardsthegoalregion.Thisbiasencouragesfasterconvergencetowardsthetargetandreducestheexplorationtime. 2.Dynamicobstacleavoidance:UAVsoftenencounterdynamicobstaclessuchasmovingvehiclesorhumans.Theimprovedalgorithmincorporatesreal-timeobstacledetectionandavoidancetechniques.Itusessensorydatafromonboardsensorsorexternalsourcestodetectandavoidobstaclesduringtheplanningprocess,ensuringsafeandcollision-freetrajectories. 3.Pathsmoothing:TherawtrajectorygeneratedbyRRT-C