Abstract
This paper develops methodology and technique for pose tracking of an autonomous mobile robot (AMR) using a laser scanner. A low-complexity and accurate pose-tracking EKF-based algorithm is proposed using a simple rectangular model and a 2-D laser scanner. By continuously updating the robot's pose and matching the laser data with the environmental model, we find that the outliers can be filtered out effectively by validation gate. Moreover, a Range-Weighted Hough Transform (RWHT) is used to extract the modeled lines from the clutter data. Numerous simulations and experimental results are provided to verify the feasibility and effectiveness of the proposed pose-tracking method.
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