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A novel approach to multi-robot cooperative map-building in complex environments is presented in this paper. The approach lets all robots operate individually and then tries to merge the different local grid maps into a single global one. Without using any pose information of the robots, the process of map merging is performed by measuring the similarity between grid maps. A distance transform and an improved genetic algorithm are used to effectively search the maximum overlap at which the local maps can be joined together. Experimental results show the feasibility and effectiveness of our approach in complex environments.