Continuous Map-aware Particle Filter in Off-road Environment
| DOWNLOAD | DOI: 10.62897/COS2024.2-1.175 |
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Author: Tamás V. Michaletzky, Tamás Kozma, Balázs Kósa, Tamás Fébert, Viktor Remeli, Viktor Tihanyi Széchenyi István University, Hungary michaletzky.tamas@techtra.hu |
Abstract: Accurate localization is a persistent challenge in mobile object tracking, particularly in environ-ments characterized by uneven sensor coverage and inconsistent sensor reliability. This study explores the integration of map-aware particle filters, leveraging map data to enhance posi-tioning accuracy by assigning higher probabilities to positions near defined paths and lower probabilities to off-road locations. Experiments are made in a simulated environment to test the filters under different sensor reliability. A comparative analysis with traditional particle filtering methods demonstrates that the map-aware approach, when appropriately parameterized for the given environmental condition, significantly improves positioning accuracy, emphasizing its potential for enhancing mobile tracking performance in complex environments. The two proposed methods, DMAPF and CMAPF are also compared under multiple scenarios.
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