For　the　sake　of　accomplishing　the　rapidity,　safety　and　consistency　of　obstacle　avoidance　for　a　large-scale　unmanned　aerial　vehicle　(UAV)　swarm　in　a　dynamic　and　unknown　3D　environment,　this　paper　proposes　a　flocking　control　algorithm　that　mimics　the　behavior　of　starlings.　By　analyzing　the　orderly　and　rapid　obstacle　avoidance　behavior　of　a　starling　flock,　a　motion　model　inspired　by　a　flock　of　starlings　is　built,　which　contains　three　kinds　of　motion　patterns,　including　the　collective　pattern,　evasion　pattern　and　local-following　pattern.　Then,　the　behavior　patterns　of　the　flock　of　starlings　are　mapped　on　a　fixed-wing　UAV　swarm　to　improve　the　ability　of　obstacle　avoidance.　The　key　contribution　of　this　paper　is　collective　and　collision-free　motion　planning　for　UAV　swarms　in　unknown　3D　environments　with　dynamic　obstacles.　Numerous　simulations　are　conducted　in　different　scenarios　and　the　results　demonstrate　that　the　proposed　algorithm　improves　the　speed,　order　and　safety　of　the　UAV　swarm　when　avoiding　obstacles.