An outdoor guidepath navigation system for AMRs based on robust detection of magnetic markers

This paper presents an outdoor guidepath navigation system for autonomous mobile robots (AMR) that use permanent magnetic markers embedded in the ground. The odometric data provided by the wheel encoders is fused with the data from magnetic markers. The extended Kalman filter (EKF) was chosen for the fusion process. The AMR is equipped with a magnetic sensing ruler (MSR) developed at ISR-UC that is able to perform a robust detection of magnetic markers. The detection is based on a 3-D algorithm that includes longitudinal-fitting detection (LFD), and cross-fitting detection (CFD). Both, the LFD and the CFD are based on the least squares fitting (LSF) of the measurement data with the 3-D model of the vertical magnetic field. The experimental results with Robchair (intelligent wheelchair being developed at ISR-UC) primarily show that the detection system is robust, since it is able to detect true magnetic markers, and to eliminate noisy magnetic distortions and false markers. The design, and implementation of the navigation algorithm in the Robchair were carried out, and results are presented.