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Research on map merging for multi-robotic system based on RTM

Ke Wang, Songmin Jia, Yuchen Li, Xiuzhi Li, Bing Guo

Year
2012
Citations
25

Abstract

Multi-robotic system is widely used in exploring in large-scale unknown environment and performing the complex tasks. This paper presents a method of local map merging for Multi-robotic system using RTM as communication platform. We integrate Scale-Invariant Feature Transform (SIFT) feature matching information with iterative closest point (ICP) algorithm to realize the local map merging. We use the USARSim as simulation platform to realize topological map and map merging for the environment in which mobile robots moving using the proposed method. The paper details the architecture of the proposed method and gives some experiments to verify the effectiveness.

Keywords

Scale-invariant feature transformComputer scienceIterative closest pointArtificial intelligenceMobile robotRobotComputer visionFeature (linguistics)Scale (ratio)Matching (statistics)

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