Bootstrapping Computer Vision and Sensor Fusion for Absolute and Relative Vehicle Positioning

Autor:	Erwin Rademakers, Karel Janssen, Norddin El Ghouti, Boulaid Boulkroune, Richard P. Kleihorst
Rok vydání:	2015
Předmět:	Vehicle positioning business.industry Bootstrapping Computer science Hybrid positioning system media_common.quotation_subject Inertia Sensor fusion Feature (computer vision) Global Positioning System Computer vision Artificial intelligence Visual odometry business media_common
Zdroj:	Advanced Concepts for Intelligent Vision Systems ISBN: 9783319259024 ACIVS
Popis:	With the migration into automated driving for various classes of vehicles, affordable self-positioning upto at least cm accuracy is a goal to be achieved. Commonly used techniques such as GPS are either not accurate enough in their basic variant or accurate but too expensive. In addition, sufficient GPS coverage is in several cases not guaranteed. In this paper we propose positioning of a vehicle based on fusion of several sensor inputs. We consider inputs from improved GPS with internet based corrections, inertia sensors and vehicle sensors fused with computer vision based positioning. For vision-based positioning, cameras are used for feature-based visual odometry to do relative positioning and beacon-based for absolute positioning. Visual features are brought into a dynamic map which allows sharing information among vehicles and allows us to deal with less robust feautures. This paper does not present final results, yet it is intended to share ideas that are currently being investigated and implemented.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::6b0c351f8ff123891238a89a2ce94582 https://doi.org/10.1007/978-3-319-25903-1_21 Zobrazit plný text záznamu