Directed　Energy　Deposition　(DED)　technology　is　increasingly　favored　for　swiftly　fabricating　large　structural　components　due　to　its　high　printing　efficiency.　Despite　its　advantages,　challenges　persist　in　achieving　satisfactory　surface　finish　and　forming　precision,　hindering　its　widespread　adoption　across　industries.　To　address　these　issues,　this　paper　presents　a　novel　multi-robot　collaborative　path　planning　method　based　on　structural　primitive　partitioning.　This　method　simplifies　path　planning　complexities　and　seamlessly　integrates　into　process　planning　software,　thereby　enhancing　overall　functionality.　This　method　decomposes　complex　polygons　into　tiny　primitives　(TP),　organizing　them　into　TP　sets　based　on　bridge　and　adjacency　relations.　These　sets　are　then　structured　into　first-level　structural　TP　(F-TP)　and　second-level　structural　TP　(S-TP),　followed　by　the　establishment　of　monotonic　structural　TP　(M-TP).　A　minimum　rectangular　box　recalculates　the　filling　path　for　each　M-TP,　while　the　external　contour　path　and　internal　zigzag　path　form　a　complete　printing　path.　Additionally,　an　optimal　printing　sequence　planning　algorithm　for　multi-robot　using　a　KD-tree-based　search　algorithm　is　presented,　ensuring　the　shortest　non-productive　path　and　collision　avoidance　during　printing.　Experimental　verification　with　four　structures　of　varying　geometric　features　demonstrates　a　partitioning　accuracy　of　99.5　%　and　absence　of　surface　defects　in　the　printed　parts.　The　proposed　method　presents　a　viable　and　effective　solution　for　enhancing　the　quality　of　parts　produced　via　DED.　©　2024　Elsevier　Ltd