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A feature matching method for simultaneous localization and mapping

Xiangkui Chen, Min Jiang, Liangyu Zuo, Jiang Jian

发表年份
2017
引用次数
3

摘要

Simultaneous Localization and Mapping is an important technology which help a mobile robot to determine its location and build the environment map. Recently, the RGBD sensor is widely used in the robot, research on RGBD-SLAM becomes a hot topic. In order to calculate the movement parameters of robot, feature matching is adopted to register the two adjacent RGBD images in the video stream. This paper proposed an improved feature matching method for RGBD-SLAM. The experiment results show that, compared with the traditional SIFT feature matching methods for RGBD-SLAM, the performance of the proposed method is improved significantly.

关键词

Scale-invariant feature transformArtificial intelligenceComputer visionMatching (statistics)Feature (linguistics)Computer scienceSimultaneous localization and mappingFeature matchingMobile robotRobot

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