Find your way by observing the sun and other semantic cues

Wei Chiu Ma; Shenlong Wang; Marcus A. Brubaker; Sanja Fidler; Raquel Urtasun

doi:10.1109/ICRA.2017.7989744

Find your way by observing the sun and other semantic cues

Wei Chiu Ma, Shenlong Wang, Marcus A. Brubaker, Sanja Fidler, Raquel Urtasun

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper we present a robust, efficient and affordable approach to self-localization which requires 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 and ego-car trajectory 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.

Original language	English (US)
Title of host publication	ICRA 2017 - IEEE International Conference on Robotics and Automation
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	6292-6299
Number of pages	8
ISBN (Electronic)	9781509046331
DOIs	https://doi.org/10.1109/ICRA.2017.7989744
State	Published - Jul 21 2017
Externally published	Yes
Event	2017 IEEE International Conference on Robotics and Automation, ICRA 2017 - Singapore, Singapore Duration: May 29 2017 → Jun 3 2017

Publication series

Name	Proceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)	1050-4729

Other

Other	2017 IEEE International Conference on Robotics and Automation, ICRA 2017
Country/Territory	Singapore
City	Singapore
Period	5/29/17 → 6/3/17

ASJC Scopus subject areas

Software
Control and Systems Engineering
Artificial Intelligence
Electrical and Electronic Engineering

Online availability

10.1109/ICRA.2017.7989744

Library availability

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Ma, W. C., Wang, S., Brubaker, M. A., Fidler, S., & Urtasun, R. (2017). Find your way by observing the sun and other semantic cues. In ICRA 2017 - IEEE International Conference on Robotics and Automation (pp. 6292-6299). Article 7989744 (Proceedings - IEEE International Conference on Robotics and Automation). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICRA.2017.7989744

Find your way by observing the sun and other semantic cues. / Ma, Wei Chiu; Wang, Shenlong; Brubaker, Marcus A. et al.
ICRA 2017 - IEEE International Conference on Robotics and Automation. Institute of Electrical and Electronics Engineers Inc., 2017. p. 6292-6299 7989744 (Proceedings - IEEE International Conference on Robotics and Automation).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ma, WC, Wang, S, Brubaker, MA, Fidler, S & Urtasun, R 2017, Find your way by observing the sun and other semantic cues. in ICRA 2017 - IEEE International Conference on Robotics and Automation., 7989744, Proceedings - IEEE International Conference on Robotics and Automation, Institute of Electrical and Electronics Engineers Inc., pp. 6292-6299, 2017 IEEE International Conference on Robotics and Automation, ICRA 2017, Singapore, Singapore, 5/29/17. https://doi.org/10.1109/ICRA.2017.7989744

Ma WC, Wang S, Brubaker MA, Fidler S, Urtasun R. Find your way by observing the sun and other semantic cues. In ICRA 2017 - IEEE International Conference on Robotics and Automation. Institute of Electrical and Electronics Engineers Inc. 2017. p. 6292-6299. 7989744. (Proceedings - IEEE International Conference on Robotics and Automation). doi: 10.1109/ICRA.2017.7989744

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AB - In this paper we present a robust, efficient and affordable approach to self-localization which requires 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 and ego-car trajectory 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.

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Find your way by observing the sun and other semantic cues

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