Find Your Way by Observing the Sun and Other Semantic Cues

    Abstract

    In this paper we present a robust, efficient and affordable approach to self-localization which does not require neither GPS nor knowledge about the appearance of the world. Towards this goal, we utilize freely available cartographic maps and derive a probabilistic model that exploits semantic cues in the form of sun direction, presence of an intersection, road type, speed limit as well as the ego-car trajectory in order to produce very reliable localization results. Our experimental evaluation shows that our approach can localize much faster (in terms of driving time) with less computation and more robustly than competing approaches, which ignore semantic information.

    Authors

    Wei-chiu Ma, Shenlong Wang, Markus Brubaker, Sanja Fidler, Raquel Urtasun

    Conference

    ICRA 2017

    Full Paper

    ‘Find Your Way by Observing the Sun and Other Semantic Cues’ (PDF)

    Uber ATG

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    Wei-Chiu Ma
    Wei-Chiu Ma is a PhD student at MIT advised by Prof. Antonio Torralba. His research interests lie in the intersection of computer vision and machine learning, in particular low-level vision and 3D vision. He also works part-time at Uber ATG Toronto with Prof. Raquel Urtasun to apply his research to self-driving vehicles.
    Shenlong Wang
    Shenlong Wang is research scientist at Uber ATG Toronto working on the development of self-driving cars. He is also a PhD student at University of Toronto. His advisor is Prof. Raquel Urtasun. He has a broad interest in computer vision, machine learning and robotics. He is particularly interested in 3D vision and deep structured models.
    Raquel Urtasun
    Raquel Urtasun is the Chief Scientist for Uber ATG and the Head of Uber ATG Toronto. She is also a Professor at the University of Toronto, a Canada Research Chair in Machine Learning and Computer Vision and a co-founder of the Vector Institute for AI. She is a recipient of an NSERC EWR Steacie Award, an NVIDIA Pioneers of AI Award, a Ministry of Education and Innovation Early Researcher Award, three Google Faculty Research Awards, an Amazon Faculty Research Award, a Connaught New Researcher Award, a Fallona Family Research Award and two Best Paper Runner up Prize awarded CVPR in 2013 and 2017. She was also named Chatelaine 2018 Woman of the year, and 2018 Toronto’s top influencers by Adweek magazine