Enhanced-spectrum-based map merging for multi-robot systems

Abstract

Abstract This paper addresses the problem of grid map merging for multi-robot systems, which can be resolved by acquiring the map transformation matrix (MTM) among robot maps. Without the initial correspondence or any rendezvous among robots, the only way to acquire the MTM is to find and match the common regions of individual robot maps. This paper proposes a novel map merging technique which is capable of merging individual robot maps by matching the spectral information of robot maps. The proposed technique extracts the spectra of robot maps and enhances the extracted spectra using visual landmarks. Then, the MTM is accurately acquired by finding the maximum cross-correlation among the enhanced spectra. Experimental results in outdoor environments show that the proposed technique was performed successfully. Also, the comparison result shows that the map merging errors were significantly reduced by the proposed technique. Keywords: map mergingenhanced spectrummulti-robot systems Acknowledgments This work was supported in part by a Korea Science and Engineering Foundation (KOSEF) NRL Program grant funded by the Korean government (No. R0A-2008-000-20004-0), and in part by the ASRI, and in part by the Brain Korea 21 (BK21) Project, and in part by the Industrial Foundation Technology Development Program of MKE/KEIT [Development of CIRT (Collective Intelligence Robot Technologies)].