When　a　mobile　robot　navigates　in　unknown　environment,　the　location　of　the　robot　is　unknown　and　the　environment　information　is　also　unpredictable.　To　solve　these　uncertain　problems,　the　method　of　simultaneous　localization　and　mapping　based　on　improved　particle　filter　in　grid　map　was　presented.　Bayes＇　rules　were　applied　to　update　environment　information　and　the　improved　particle　filter　was　applied　to　the　mobile　localization.　When　the　robot　detects　the　environment,　it　updates　map　information　and　localizes　its　position　by　turns.　The　simulation　result　shows　the　method　enhances　the　real-time　performance　of　the　improved　algorithm.　With　the　method,　the　robot　localizes　itself　accurately　as　well　as　building　grid　map　with　higher　accuracy.　The　proposed　algorithm　is　effective　and　reliable　to　realize　simultaneous　localization　and　mapping.