Aiming　at　the　environment　cognition　and　navigation　problem　of　autonomous　mobile　robots　in　unknown　environment,　a　cognitive　map　learning　model　is　proposed　based　on　hippocampal　place　cells,　which　can　memorize　and　map　surroundings.　The　model　uses　the　self-organizing　feature　map　as　the　basic　structure.　Each　hippocampal　place　cell　is　represented　by　a　neural　node.　The　robot　builds　up　the　hippocampal　place　cells　layer　through　environment　exploration.　The　simulation　results　show　that　the　model　has　self-learning　ability,　which　enables　robots　to　acquire　environment　knowledge　and　establish　a　complete　cognitive　map　gradually　like　human　beings　and　animals,　making　the　robot＇s　environment　cognition　and　navigation　process　become　more　bionic　and　intelligent.　©　2018　Association　for　Computing　Machinery.