For　exploring　the　interior　unknown　environment,　by　using　an　autonomous　mobile　robot　this　paper　proposes　a　high-effect　autonomous　environment　exploration　algorithm　based　on　a　hybrid　topological-metric　map.　The　topological　map　based　on　environment　Opening-Points　is　built　in　real-time　according　to　current　sensor　information.　The　optimal　instant　target　is　selected　as　the　exploration　direction　for　the　next　step　by　analyzing　and　dealing　with　the　Opening-Points.　In　the　framework　of　Rao-Blackwellized　particle　filter　(RBPF),　the　grid　map　based　Simultaneous　Localization　and　Mapping　(SLAM)　is　introduced　into　the　autonomous　exploration　process　of　the　mobile　robot,　which　provides　the　accurate　position　estimate　to　improve　the　position　accuracy　of　the　topological　node　effectively　and　complete　the　exploration　task　smoothly.　The　exploration　algorithm　based　on　the　above　two　strategies　gives　consideration　to　both　accuracy　and　efficiency.　The　validity　and　practicability　of　the　proposed　exploration　approach　was　validated　by　a　lot　of　experiments　on　the　mobile　robot　Pioneer3-DX.