NDLI: Self calibration of a vision system embedded in a visual SLAM framework

Content Provider	IEEE Xplore Digital Library
Author	Joly, Cyril Rives, Patrick
Copyright Year	2011
Description	Author affiliation: INRIA Sophia Antipolis Méditerranée, 2004 route des lucioles BP93, Cedex, France (Joly, Cyril; Rives, Patrick)
Abstract	This paper presents a novel approach to self calibrate the extrinsic parameters of a camera mounted on a mobile robot in the context of fusion with the odometry sensor. Calibrating precisely such a system can be difficult if the camera is mounted on a vehicle where the frame is difficult to localize precisely (like on a car for example). However, the knowledge of the camera pose in the robot frame is essential in order to make a consistent fusion of the sensor measurements. Our approach is based on a Simultaneous Localization and Mapping (SLAM) framework: the estimation of the parameters is made when the robot moves in an unknown environment which is only viewed by the camera. First, a study of the observability properties of the system is made in order to characterize conditions that its inputs have to satisfy to make the calibration process possible. Then, we show on a real experiment with an omnidirectional camera the validity of the conditions and the quality of the estimation of the 3D pose of the camera with respect to the odometry frame.
Starting Page	3320
Ending Page	3326
File Size	610111
Page Count	7
File Format	PDF
ISBN	9781612844541
ISSN	21530858
e-ISBN	9781612844565
DOI	10.1109/IROS.2011.6095029
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cameras Robot vision systems Observability Trajectory Simultaneous localization and mapping Robot kinematics
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Computer Science Applications Computer Vision and Pattern Recognition Software

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