How　rats　achieve　goal-oriented　navigation　is　a　hot　research　topic　in　neuroscience.　Inspired　by　neurophysiological　research,　this　paper　proposes　a　brain-like　navigation　method　inspired　by　the　spatial　cells’　cognitive　mechanism.　Firstly,　a　neural　computational　model　of　the　entorhinal-hippocampal　structure　is　constructed　for　path　integration.　Subsequently,　a　visual　pathway　computational　model　is　constructed　to　correct　the　accumulated　errors.　Finally,　a　self-organizing　computational　model　of　hippocampal　CA1　place　cells　is　constructed　to　optimize　the　navigation　path.　In　order　to　verify　the　model,　this　paper　designs　the　2-D　simulation　experiment,　and　the　proposed　model　is　also　compared　with　other　models.　The　experimental　results　show　that　the　proposed　model　cannot　only　make　the　navigation　process　more　robust　by　using　visual　information.　Moreover,　it　can　gradually　optimize　the　navigation　path　through　the　self-organized　activity　of　hippocampal　CA1　place　cells,　thus　improving　the　efficiency　of　navigation.　©　2022　Elsevier　Ltd