Abstract
This paper addresses the issues of the autonomous exploration and grid-topology hybrid map building of mobile robots in large-scale environments. First, in order to improve the defect of the original method in the special environment, a way to extract the target point based on the free area is proposed. Then, we use the information gain and the extraction method of fast back to the initial topological node to evaluate the target point, so as to solve the problem that the long time no loop closure detection leads to the failure of the map building. Finally, we propose an improved method of building and optimizing the real-time topological map based on the information of the laser data and grid map, which makes the grid-topology hybrid map more concise and the exploration process more efficient. The effectiveness of the proposed autonomous exploration and grid-topology hybrid map building method for mobile robots in unknown environments is verified by experiments.
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