With　the　wide　application　of　automated　guided　vehicles　(AGVs)　in　large　scale　outdoor　scenarios　with　complex　terrain,the　collaborative　work　of　a　large　number　of　AGVs　becomes　the　main　trend.　The　effective　multi-agent　path　finding　(MAPF)　algorithm　is　urgently　needed　to　ensure　the　efficiency　and　realizability　of　the　whole　system.　The　complex　terrain　of　outdoor　scenarios　is　fully　considered　by　using　different　values　of　passage　cost　to　quantify　different　terrain　types.　The　objective　of　the　MAPF　problem　is　to　minimize　the　cost　of　passage　while　the　Manhattan　distance　of　paths　and　the　time　of　passage　are　also　evaluated　for　a　comprehensive　comparison.　The　pre-path-planning　and　real-time-conflict　based　greedy　(PRG)　algorithm　is　proposed　as　the　solution.　Simulation　is　conducted　and　the　proposed　PRG　algorithm　is　compared　with　waiting-stop　A∗　and　conflict　based　search　(CBS)　algorithms.　Results　show　that　the　PRG　algorithm　outperforms　the　waiting-stop　A∗　algorithm　in　all　three　performance　indicators,and　it　is　more　applicable　than　the　CBS　algorithm　when　a　large　number　of　AGVs　are　working　collaboratively　with　frequent　collisions.　©　2023　Inst.　of　Scientific　and　Technical　Information　of　China.　All　rights　reserved.