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Miguel Ángel Muñoz-Bañón

3 accepted papers

2024

Geo-Localization Based on Dynamically Weighted Factor-Graph

Miguel Ángel Muñoz-Bañón, Alejandro Olivas, Edison Velasco-Sánchez, Francisco A. Candelas, Fernando Torres
RA-L 2024

Feature-based geo-localization relies on associating features extracted from aerial imagery with those detected by the vehicle's sensors. This requires that the type of landmarks must be observable from both sources. This lack of variety of feature types generates poor representations that lead to o

Cited by 7Source ↗Scholar ↗
2022

DA-LMR: A Robust Lane Marking Representation for Data Association

Miguel Ángel Muñoz-Bañón, Jan-Hendrik Pauls, Haohao Hu, Christoph Stiller
ICRA 2022poster

While complete localization approaches are widely studied in the literature, their data association and data representation subprocesses usually go unnoticed. However, both are a key part of the final pose estimation. In this work, we present DA-LMR (Delta-Angle Lane Marking Representation), a robus…

Cited by 5Source ↗Scholar ↗
2022

Robust Self-Tuning Data Association for Geo-Referencing Using Lane Markings

Miguel Ángel Muñoz-Bañón, Jan-Hendrik Pauls, Haohao Hu, Christoph Stiller, Francisco A. Candelas, Fernando Torres
RA-L 2022

Localization in aerial imagery-based maps offers many advantages, such as global consistency, geo-referenced maps, and the availability of publicly accessible data. However, the landmarks that can be observed from both aerial imagery and on-board sensors is limited. This leads to ambiguities or alia

Cited by 7Source ↗Scholar ↗