Mobile　manipulators　have　been　widely　used　in　modern　industrial　fields　due　to　their　advantages　of　large　operating　workspace　and　high　motion　dexterity.　For　the　application,　the　path　planning　has　been　a　core　foundation　for　its　motion　control.　However,　as　the　environmental　complexity　and　performance　requirements　increase,　existing　methods　are　limited　by　low　execution　efficiency,　and　lack　of　comprehensive　consideration　of　motion　performances.　A　motion　planning　technique　is　proposed　for　mobile　manipulators　with　continuous　trajectory　task.　In　this　technique,　a　hierarchical　constraints　dimension　reduction　(HCDR)　strategy　is　presented　based　on　the　task　decomposition　and　performance　requirements　analysis　of　each　stage.　HCDR　strategy　aims　to　improve　the　execution　efficiency　of　the　algorithm　through　local　operations　of　performance　constraints　and　the　local　simplification　of　the　distance　calculation　at　different　stages　of　the　task.　Models　of　inverse　kinematics　and　performance　indexes　are　established　to　provide　basis　for　constraint　conditions,　including　distance　models　with　different　accuracy,　manipulability　index　model　and　trajectory　tracing　error　model.　Two　optimization　strategies　are　presented　to　solve　the　motion　planning　problem　considering　the　overall　performance　of　the　system.　And　simulation　results　show　that　the　three-level　strategy　has　the　higher　convergence　efficiency　than　the　bi-level　strategy,　as　well　as　can　guarantee　the　motion　performance　of　the　system.