¹Jinan University/ College of Information Science and Technology, Guangzhou, China
²Guangdong Food and Drug Vocational College/ Department of Software, Guangzhou, China

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Abstract—In this paper, an efficient approach is proposed for loop-closure detection in robot visual SLAM. The method uses mutual information to measure similarity between current view and key frames in an appearance map, and evaluates candidate loop-closure locations in particle filter framework. Specially, the implementation of particle filter is accelerated through updating a set of weight vector of particles, and three threshold indicators are used to select loop-closure candidates and verify loop-closure location. The comparative experiments on a popular dataset verify the high efficiency of our method which is more simple and accurate than the popular bag-of-words (BoW) for loopclosure detection.

Index Terms—Mobile robot, visual SLAM, loop-closure detection, mutual information, particle filter.

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Cite: Ning Liu and Junjun Wu, "Visual Loop Closure Detection with Scene Mutual Information for Mobile Robot," Journal of Computers vol. 9, no. 11, pp. 2642-2647, 2014.