The　firing　of　spatial　cells　in　the　entorhinal-hippocampal　structure　is　believed　to　enable　the　formation　of　a　cognitive　map　for　the　environment.　Inspired　by　the　spatial　cognitive　mechanism　of　the　rat＇s　brain,　the　authors　proposed　a　real-time　cognitive　map　construction　method　based　on　the　entorhinal-hippocampal　working　mechanism.　Firstly,　based　on　the　physiological　properties　of　the　rat＇s　brain,　the　authors　constructed　an　entorhinal-hippocampal　CA3　neurocomputational　model　for　path　integration.　Then,　the　transformation　relationship　between　the　cell　plate　and　the　real　environment　is　used　to　solve　the　robot＇s　position.　Path　integration　inevitably　generates　cumulative　errors,　which　require　loop-closure　detection　and　pose　optimisation　to　eliminate　errors.　To　solve　the　problem　that　the　RatSLAM　algorithm　is　slow　in　pose　optimisation,　the　authors　proposed　a　pose　optimisation　method　based　on　a　multi-layer　CA1　place　cell　to　improve　the　speed　of　pose　optimisation.　To　validate　the　method,　the　authors　designed　simulation　experiments,　dataset　experiments,　and　physical　experiments.　The　experimental　results　showed　that　compared　to　other　brain-like　SLAM　algorithms,　the　authors’　method　possesses　outstanding　performance　in　path　integration　accuracy　and　map　construction　speed.　As　a　result,　the　authors’　method　can　endow　mobile　robots　with　the　ability　to　quickly　and　accurately　construct　cognitive　maps　in　complex　and　unknown　environments.　©　2024　The　Authors.　Cognitive　Computation　and　Systems　published　by　John　Wiley　&　Sons　Ltd　on　behalf　of　The　Institution　of　Engineering　and　Technology　and　Shenzhen　University.