The　granularity　partition　for　functional　modules　is　a　fundamental　research　topic　in　robot　distributed　control　technology.　How　to　evaluate　the　module　partition　scheme　with　different　granularity,　and　then　obtain　the　optimum　scheme　is　the　urgent　problem.　In　this　paper,　we　proposed　a　novel　evaluation　strategy　for　the　granularity　partition　of　functional　modules　in　robotic　system　using　RTM　as　control　platform　based　on　D-S　evidence　theory.　The　fuzzy　clustering　algorithm　is　primarily　used　to　get　the　collection　of　granularity　partition　schemes　for　RT　Components　encapsulated　by　the　platform　of　OpenRTM.　As　the　two　source　of　evidence,　the　indices　of　cohesion　and　coupling　for　the　robotic　system　are　achieved　to　measure　the　degree　of　module　independence　by　analyzing　the　correlation　matrix　of　RT　Components.　Then　the　Dempster＇s　combination　rule　and　the　priority　method　for　utility　intervals　are　applied　to　obtain　the　optimal　partition　granularity.　In　the　end,　the　effectiveness　and　progressiveness　of　the　novel　evaluation　strategy　are　verified　by　applying　it　to　the　robotic　3D　mapping　system.