This paper presents a system that integrates Invariant Extended Kalman Filters with onboard sensors and map-based corrections. The system combines multiple sensors, such as an Inertial Measurement Unit and a speedometer, to improve accuracy and robustness during gaps in the map. The proposed architecture takes into consideration the different nature of each measurement used during the update step, such as map-based measurements in the world-frame and speedometer measurements in the body-frame. The experimental evaluations were conducted in diverse driving conditions. The proposed system consistently outperformed traditional solutions based on extended Kalman filters, sustaining low relative translational errors during map outages.
Robust Land Vehicle Positioning with Invariant Kalman Filters and Map-Based Corrections
2023-09-24
8070087 byte
Conference paper
Electronic Resource
English
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