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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.