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Visual Localization of Inspection Robot Using Extended Kalman Filter and Aruco Markers

Jingxiang Zheng, Shusheng Bi, Bo Cao, Dongsheng Yang

发表年份
2018
引用次数
14

摘要

This paper investigates a localization technology based on Aruco Markers for substation inspection robot. Extended Kalman Filter(EKF) algorithm is used to fuse odometer information and camera measurement data from detection of Aruco markers. The experiment results show that the localization problem can be solved by EKF localization based on Aruco markers efficiently. The localization algorithm can provide the inspection robot with relatively accurate position information and shield the impact of the dynamic environment.

关键词

OdometerExtended Kalman filterComputer visionArtificial intelligenceFuse (electrical)Kalman filterSimultaneous localization and mappingComputer scienceRobotMonte Carlo localization

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