Localization
Efficient and effective multi-sensor approaches help localize the self-driving vehicle within the HD map in real time. Our research focuses on LiDAR point clouds, camera imagery and other sources of information to boost the robustness of localization algorithms.
Recent ATG R&D publications
Exploiting Sparse Semantic HD Maps for Self-Driving Vehicle Localization
Wei-Chiu Ma*, Ignacio Tartavull*, Ioan Andrei Barsan*, Shenlong Wang*, Min Bai, Gellert Mattyus, Namdar Homayounfar, Shrinidhi Kowshika Lakshmikanth, Andrei Pokrovsky, Raquel Urtasun (IROS 2019)
Learning to Localize Through Compressed Binary Maps
Xinkai Wei*, Ioan Andrei Bârsan*, Shenlong Wang*, Julieta Martinez, Raquel Urtasun (CVPR 2019)
Learning to Localize Using a LiDAR Intensity Map
Ioan Andrei Bârsan*, Shenlong Wang*, Andrei Pokrovsky, Raquel Urtasun (CORL 2018, spotlight)
R&D Homepage
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