This　article　presents　a　resilient　formation　control　framework　for　networked　nonholonomic　mobile　robots　(NMRs)　that　enables　long-time　recovery　abilities　subject　to　denial-of-service　(DoS)　attacks　by　taking　advantage　of　the　Koopman　operator.　Due　to　the　intermittent　interruption　of　communication　under　DoS,　the　transmitted　signals　among　the　networked　NMRs　are　incomplete.　In　the　lifted　space,　the　infinite-dimensional　Koopman　operator　is　employed　to　capture　a　linear　characteristic　of　the　missed　signals　from　the　available　signals.　Specifically,　a　data-driven　cost　function　is　developed　to　approximate　the　infinite-dimensional　Koopman　operator,　allowing　long-term　recovery　capabilities　for　the　missed　signals,　where　the　useful　historical　data　is　identified　by　an　event-triggered　mechanism　(ETM).　Then,　the　least-squares　method　is　implemented　to　calculate　a　finite-dimensional　approximation　of　the　Koopman　operator.　Once　DoS　attacks　are　active,　the　missed　signals　are　recovered　forward　from　the　latest　received　signals　through　the　approximation　Koopman　operator.　Furthermore,　according　to　the　recovered　and　transmitted　signals,　the　resilient　formation　controller　with　a　variable　gain　takes　into　account　the　convergence　rate　and　the　steady　state　formation　error.　The　Lyapunov　theorem　is　introduced　to　prove　that　the　formation　error　quickly　converges　to　the　minor　compact　set.　A　distributed　DoS　attack　example　is　conducted　to　validate　the　efficiency　and　superiority　in　numerical　simulation,　and　the　proposed　method　is　implemented　on　the　real　networked　NMRs.