Multi-sensor Fusion Localization Method Enhanced by Artificial Marker
In recent years,with the rapid advancement of robotics technology,the localization algorithms for mobile robots have been continuously evolving and improving.Addressing the issues of stability and accuracy in existing mobile ro-bot localization algorithms within indoor degraded environments,a multi-sensor fusion localization method enhanced with ar-tificial markers,utilizing a quad-lens panoramic camera,single-line LiDAR,and inertial measurement unit(IMU)is pro-posed in this paper.This method employs the GTSAM factor graph optimizer to co-optimize the IMU preintegration factors,LiDAR odometry factors,and AprilTag projection factors,achieving smooth motion state estimation of the mobile robot.Ex-periment results show that the proposed method significantly improves both the positioning accuracy and stability compared to traditional methods such as the Cartographer and AprilTag_ros.The multi-sensor fusion approach,enhanced by artificial markers,not only eliminates cumulative errors but also resolves pose drift issues.It effectively resolves the problem of lo-calization loss when mobile robots navigate tunnels,long straight corridors and other similar degraded settings.
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