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Research on SLAM of indoor mobile robot assisted by AR code landmark

Cong Gu, Hongjian Zhao, Junfeng Yuan, Bowen Teng, Chenghua Tian

Year
2021
Citations
4
Access
Open access

Abstract

Abstract When mobile robots use odometer method to locate and map simultaneously in large-scale indoor scenes, there are some problems, such as large accumulated error of odometer, low positioning accuracy due to unreliable information, and large difference between the mapping results and the real environment. In view of the above problems, this paper proposes a method to correct the accumulated error of odometer with the aid of AR code artificial landmark, so as to meet the requirements of high-precision positioning and mapping of mobile robots. Using the particle filter algorithm based on Rao-Blackwellized to perform SLAM in indoor corridors, the comparison of experimental results proves that the method based on AR code landmarks can obtain high-precision positioning when the robot is running at a long distance, and the mapping results are similar to the real environment, the trajectory accuracy of the mobile robot is improved by about 8%.

Keywords

OdometerLandmarkComputer visionComputer scienceSimultaneous localization and mappingMobile robotArtificial intelligenceCode (set theory)RobotParticle filter

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