RFID-augmentation for improving long-term pose accuracy of an indoor navigating robot

Abstract

This paper presents a Radio Frequency based system for handling long-term drift of pose estimates for a robot performing odometer-based navigation in an indoor environment. The indoor environment is augmented with RFID tags and their associated door-markers to form a partially structured environment. To enhance the performance of the odometry, we adopted a Least Squares calibration approach to mitigate the effect of the systematic errors. The residual errors, mainly non-systematic, are handled by intermittent resetting of the robot's pose based on the global positioning references designed with the RFID tags and their associated door-markers. The results reveal that the long-term confidence in the estimated position improves about six times with this approach.