An MICP Algorithm for 3D Map Reconstruction Based on 3D Cloud Information of Landmarks
This paper aims to reconstruct 3D map based on environmental 3D cloud information of landmarks. A Modified Iterative Closest Point (MICP) algorithm is proposed to apply for merging point clouds through a transformation matrix with values updated using the robot’s position. In particular, reconstruction of 3D map is performed based on the location information of landmarks in an indoor environment. In addition, the transformation matrix obtained using the MICP algorithm will be up-dated again whenever the error among the point clouds is greater than one setup threshold. The result is that the environmental 3D map is reconstructed more accurately compared using the MICP. The experimental results showed that the effectiveness of the proposed method in improving the quality of reconstructing 3D cloud map.
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