A　fast　global　registration　algorithm　for　3D　point　cloud　is　proposed,　which　is　used　to　estimate　the　rigid　pose　relationship　of　any　two　sets　of　similar　point　clouds　in　space.　First,　the　three　principal　component　vectors　of　two　groups　of　point　clouds　are　calculated　to　form　their　own　principal　component　(PC)　coordinate　systems　with　their　respective　center　points.　Then,　in　order　to　obtain　the　approximate　pose　relationship　between　the　two　similar　groups　of　point　clouds,　the　coordinate　transformations　of　the　two　groups　of　point　clouds　are　respectively　performed,　and　the　directions　corresponding　to　the　PC　coordinate　axes　are　corrected　by　the　mean　of　Euclidean　distances　of　some　close　points.　After　the　above　coarse　registration,　the　two　groups　of　point　clouds　can　be　matched　fast　and　accurately　at　arbitrary　position　by　the　fast　iterative　closest　point　(ICP)　algorithm.　The　experimental　results　show　that　the　proposed　method　can　achieve　global　registration　for　any　two　sets　of　point　clouds　with　similar　shape　and　completeness　at　any　position　in　any　pose,　and　has　higher　speed　and　accuracy.　©　2018　Universitat　zu　Koln.　All　rights　reserved.