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LSH-RANSAC: Incremental Matching of Large-Size Maps

Tanaka Kanji, Ken‐ichi Saeki, Mamoru Minami, Ueda Takeshi

发表年份
2010
引用次数
3
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摘要

This paper presents a novel approach for robot localization using landmark maps. With recent progress in SLAM researches, it has become crucial for a robot to obtain and use large-size maps that are incrementally built by other mapper robots. Our localization approach successfully works with such incremental and large-size maps. In literature, RANSAC map-matching has been a promising approach for large-size maps. We extend the RANSAC map-matching so as to deal with incremental maps. We combine the incremental RANSAC with an incremental LSH database and develop a hybrid of the position-based and the appearance-based approaches. A series of experiments using radish dataset show promising results.

关键词

RANSACComputer scienceLandmarkMatching (statistics)Artificial intelligenceRobotComputer visionPosition (finance)Pattern recognition (psychology)Image (mathematics)

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