Indoor Localization Method for a Mobile Robot Using LiDAR and a Dual AprilTag

Yuan Heng Huang, Chin Te Lin

Research output: Contribution to journalArticlepeer-review


Global localization is one of the important issues for mobile robots to achieve indoor navigation. Nowadays, most mobile robots rely on light detection and ranging (LiDAR) and adaptive Monte Carlo localization (AMCL) to realize their localization and navigation. However, the reliability and performance of global localization only using LiDAR are restricted due to the monotonous sensing feature. This study proposes a global localization approach to improve mobile robot global localization using LiDAR and a dual AprilTag. Firstly, the spatial coordinate system constructed with two neighboring AprilTags is applied as the reference basis for global localization. Then, the robot pose can be estimated by generating precise initial particle distribution for AMCL based on the relative tag positions. Finally, in pose tracking, the count and distribution of AMCL particles, evaluating the certainty of localization, is continuously monitored to update the real-time position of the robot. The contributions of this study are listed as follows. (1) Compared to the localization method only using LiDAR, the proposed method can locate the robot’s position with a few iterations and less computer power consumption. (2) The failure localization issues due to the many similar indoor features can be solved. (3) The error of the global localization can be limited to an acceptable range compared to the result using a single tag.

Original languageEnglish
Article number1023
JournalElectronics (Switzerland)
Issue number4
StatePublished - Feb 2023


  • AprilTag
  • LiDAR
  • adaptive Monte Carlo localization (AMCL)
  • global localization
  • mobile robot


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