Map-Aided Train Navigation with IMU Measurements

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Marc-Antoine Lavoie, James Richard Forbes

Published: 01 Jan 2021, Last Modified: 06 Nov 2025IROS 2021EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Autonomous train navigation using only a low-cost MEMS IMU and a track map is considered in this paper. The approach is designed for urban rail or subway environments where GNSS measurements are unreliable or unavailable, and is intended as a baseline against which more complex sensor fusion approaches can be compared to ensure the consistency of the estimates. The estimator exploits the track motion constraint and information about position and velocity derived from centripetal acceleration and angular velocity measurements to improve the dead-reckoning solution and keep error and uncertainty bounded. In experimental validation over a 6 km run of a subway train during commuter service, the proposed approach had a maximum error of 6.0 m, validating the approach as an independent estimator.