5 citations · 11 across the 13 of their papers we have counts for
5 papers · 1 filter
Mosaic: An Extensible Framework for Composing Rule-Based and Learned Motion Planners
Nick Le Large, Marlon Steiner, Lingguang Wang +4
Safe and explainable motion planning remains a central challenge in autonomous driving. While rule-based planners offer predictable and explainable behavior, they often fail to gra…
Impact of Localization Errors on Label Quality for Online HD Map Construction
Alexander Blumberg, Jonas Merkert, Richard Fehler +4
High-definition (HD) maps are crucial for autonomous vehicles, but their creation and maintenance is very costly. This motivates the idea of online HD map construction. To provide…
MapGCLR: Geospatial Contrastive Learning of Representations for Online Vectorized HD Map Construction
Jonas Merkert, Alexander Blumberg, Jan-Hendrik Pauls +1
Autonomous vehicles rely on map information to understand the world around them. However, the creation and maintenance of offline high-definition (HD) maps remains costly. A more s…
Robust Self-Tuning Data Association for Geo-Referencing Using Lane Markings
Miguel Ángel Muñoz-Bañón, Jan-Hendrik Pauls, Haohao Hu +3
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 la…
DA-LMR: A Robust Lane Marking Representation for Data Association
Miguel Ángel Muñoz-Bañón, Jan-Hendrik Pauls, Haohao Hu +1
While complete localization approaches are widely studied in the literature, their data association and data representation subprocesses usually go unnoticed. However, both are a k…