Abstract: Anewmissionplanningalgorithmwasproposedtodealwiththeproblemsoflowidentifiabilityofdynamicuncertaintiesandsinglenessofresponsestrategyintraditionalmissionplanningalgorithmsfordeepspaceexplorer.Firstly，thelevelofdisturbancegeneratedbydynamicuncertaintieswasdividedintofourlevels.Fuzzyneuralnetworkwasusedtoevaluatethelevelofuncertainties，anditcanhelptochoosetheappropriateresponsestrategy.Secondly，alocalmissionrepairplanningmethodbasedonhierarchicaltasknetwork（HTN）wasproposedtoredecomposetheinvalidcomplexmissionscausedbythedisturbanceofuncertaintieswhentheresponsestrategywasrepairplanningstrategy.Finally，computersimulationresultsshowthattheproposedalgorithmcaneffectivelyevaluateandrespondtodeepspacedynamicuncertainfactors，andthereforeimprovethereliabilityandflexibilityofthemissionplanningalgorithm.

Key words: deepspaceexploration, missionplanning, dynamicuncertainties, fuzzyneuralnetwork, hierarchicaltasknetwork