Multi-robot environment exploration based on label maps building via recognition of frontiers

This paper presents a new approach to multi-robot environment exploration based on label maps building through recognition of frontiers. At first, the model of multi-robot environment exploration is built and analysed, in which, the label map building, the formation and role modeling, and the task assignment are synthetically considered. Then the behavior coordination towards exploration process is studied in depth according to label maps and cooperative tasks. Thus the extraction of shape context features from local maps, label map building based on frontier recognition with shape context, behavior coordination with label maps and cooperative tasks, and real time path planning and updating are integrated to make up of an effective implementing algorithm which can successfully avoid some repeated and/or redundant exploration of the same region by multiple robots. A series of simulations and real world experiments results demonstrate the performance advantages of our proposed approach so as to outperform the other methods ignoring label maps in the same conditions.

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