Abstract
This paper addresses the problem of grid map merging for multi-robot SLAM(simultaneous localization and mapping) with LiDAR(light detection and ranging). The problem becomes highly challenging if inter-robot observations, common landmarks, and the knowledge of initial relative poses are not available in the multi-robot SLAM system. This paper proposes an accurate grid map merging method with spectra-based particle swarm optimization (PSO) to solve the problem. Experimental results show that the proposed method can be conducted successfully and acquire a more accurate merged map than the existing methods.
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