The　distributed　SLAM　system　is　a　value　method　for　mobile　robot　navigation.　But　particle　impoverishment　is　inevitably　because　of　the　random　particles　prediction　and　resampling　applied　in　generic　particle　filter,　especially　in　SLAM　problem　that　involve　a　large　number　of　dimensions.　In　this　paper,　the　distributed　particle　swarm　optimized　particle　filter　was　developed　to　improve　the　SLAM　system.　The　Quantum-behaved　particle　swarm　optimized　particle　filter　was　used　to　replace　the　local　filters　in　distributed　SLAM　system.　The　detailed　process　of　the　improved　distributed　SLAM　system　was　described.　And　the　analysis　and　prove　for　the　optimized　distributed　SLAM　system　was　finished.　The　simulation　experiment　was　finished　using　the　experiment　data　come　from　an　experiment　that　taken　at　Victoria　Park.　And　the　experiment　results　show　that　the　proposed　algorithm　improved　the　virtue　of　the　DPF-SLAM　system　in　isolate　faults　and　enabled　the　system　has　a　better　tolerance　and　robustness.