In　this　paper,　we　present　an　approach　for　robot　exploration　in　large-scale　unknown　environment　by　concurrent　and　incremental　construction　of　a　hybrid　environment　model,　which　is　built　on　top　of　a　RBPF-SLAM　system.　In　our　work,　SLAM　technique　for　robot　exploration　is　based　on　laser　scan-matching　and　Rao-Blackwellized　Particle　Filter.　The　model　of　the　unknown　environment　is　structured　as　a　hybrid　representation,　both　topological　and　grid-based,　and　it　is　incrementally　built　during　the　exploration　process.　Path　planning　algorithm　based　on　topological　graph　is　used　for　the　robot＇s　exploration　task,　which　is　efficiently　optimized　even　for　very　large-scale　environments.　The　effectiveness　of　our　proposal　is　validated　by　real　experimental　results　carried　on　Pioneer　robot.