Robust Self-Tuning Data Association for Geo-Referencing Using Lane Markings
| Autor: | Miguel Angel Munoz-Banon, Jan-Hendrik Pauls, Haohao Hu, Christoph Stiller, Francisco A. Candelas, Fernando Torres |
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| Přispěvatelé: | Universidad de Alicante. Departamento de Física, Ingeniería de Sistemas y Teoría de la Señal, Automática, Robótica y Visión Artificial |
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: |
FOS: Computer and information sciences
Control and Optimization Mechanical Engineering Computer Vision and Pattern Recognition (cs.CV) Biomedical Engineering Computer Science - Computer Vision and Pattern Recognition Computer Science Applications Human-Computer Interaction Autonomous vehicle navigation Computer Science - Robotics Artificial Intelligence Control and Systems Engineering Localization Computer Vision and Pattern Recognition Robotics (cs.RO) |
| Zdroj: | RUA. Repositorio Institucional de la Universidad de Alicante Universidad de Alicante (UA) |
| Popis: | 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 aliasing during the data association. Building upon a highly informative representation (that allows efficient data association), this paper presents a complete pipeline for resolving these ambiguities. Its core is a robust self-tuning data association that adapts the search area depending on the entropy of the measurements. Additionally, to smooth the final result, we adjust the information matrix for the associated data as a function of the relative transform produced by the data association process. We evaluate our method on real data from urban and rural scenarios around the city of Karlsruhe in Germany. We compare state-of-the-art outlier mitigation methods with our self-tuning approach, demonstrating a considerable improvement, especially for outer-urban scenarios. The paper is being considered for publication in "IEEE Robotics and Automation Letters" (RA-L) |
| Databáze: | OpenAIRE |
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