Autonomous robot exploration based on hybrid environment model

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.