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Tomographic Feature-Based Map Merging for Multi-Robot Systems

Department of Electronic Engineering, Kumoh National Institute of Technology, Gumi 39177, Korea
Electronics 2020, 9(1), 107;
Received: 12 December 2019 / Revised: 2 January 2020 / Accepted: 6 January 2020 / Published: 6 January 2020
(This article belongs to the Section Systems & Control Engineering)
Multi-robot systems require collective map information on surrounding environments to efficiently cooperate with one another on assigned tasks. This paper addresses the problem of grid map merging to obtain the collective map information in multi-robot systems with unknown initial poses. If inter-robot measurements are not available, the only way to merge the maps is to find and match the overlapping area between maps. This paper proposes a tomographic feature-based map merging method, which can be successfully conducted with relatively small overlapping areas. The first part of the proposed method is to estimate a map transformation matrix using the Radon transform which can extract tomographically salient features from individual grid maps. The second part is to determine the search space using Gaussian mixture models based on the estimated map transformation matrix. The final part is to optimize an objective function modeled from tomographic information within the determined search space. Evaluation results with various pairs of individual maps produced by simulations and experiments showed that the proposed method can merge the individual maps more accurately than other map merging methods. View Full-Text
Keywords: multi-robot system; grid map merging; tomographic features multi-robot system; grid map merging; tomographic features
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Lee, H. Tomographic Feature-Based Map Merging for Multi-Robot Systems. Electronics 2020, 9, 107.

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