This　paper　presents　a　novel　extrinsic　calibration　method　based　on　four-layer　laser　and　a　camera,　In　the　case　of　camera　intrinsic　parameters　are　known,　we　can　obtain　the　corresponding　points　on　a　set　of　laser　data　and　image　feature　points　by　using　the　same　feature　that　both　captured　by　laser　and　camera,　which　followed　by　acquiring　the　extrinsic　parameters　of　sensor　sysems　according　to　the　projective　relation　between　the　laser　coordinate　and　pixel　coordinate　system.　In　order　to　make　full　use　of　advantages　of　four-layer　laser,　we　designed　a　special　calibration　board,　which　allows　us　to　solve　unique　solution　by　using　P6P　algorithm　with　only　three　different　postures.　The　precision　of　solutioin　depends　on　accuracy　of　feature　points,　which　can　be　affected　by　following　reasons.　1)　Lack　of　optimization　on　extracted　features　points.　Because　the　interval　between　adjacent　scan　points,　which　may　not　just　fall　on　the　edge　of　slit,　is　about　20mm,　so　deviation　range　of　the　feature　points　in　Y　axis　direction　of　the　radar　coordinate　is　about　0　similar　to　10mm.　2)　The　extracted　feature　points　are　approximate.　Because　the　ideal　feature　point　should　be　located　in　the　middle　of　the　edge　of　slit,　of　which　the　width　is　5mm,　so　deviation　range　of　the　feature　points　in　Z　axis　direction　of　the　radar　coordinate　is　about　0　similar　to　3mm.　The　experimental　results　show　that　the　average　projection　error　is　about　30pixels,　while　that　of　which　in　the　state　of　the　art　achieve　6pixels([1]),　which　is　mainly　occured　by　no　optimal　processing.　The　advantage　of　this　method　is　simple　and　reliable,　and　the　cost　of　the　sensors　is　low　as　well,　which　allows　it　can　be　used　in　scenes　such　as　off-road　vehicle　autonomous　navigation.