Fusing Monocular Information in Multicamera SLAM

• Published in: IEEE transactions on robotics Vol. 24; no. 5; pp. 958 - 968
• Main Authors: Sola, J., Monin, A., Devy, M., Vidal-Calleja, T.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-10-2008; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Automatic; Calibration; Cameras; Crystallization; Delay estimation; Engineering Sciences; Filtering; Firing; Image sequence analysis; Information; Kalman filtering; Kalman filters; Localization; Machine vision; Mapping; Monocular vision; Outdoor; Robot vision systems; Sensors; Simultaneous localization and mapping; stereovision; Visual; Kalman filtering; robot vision systems; Calibration; stereovision; image sequence analysis; machine vision; Kalman fil- tering
• ISSN: 1552-3098; 1941-0468
• DOI: 10.1109/TRO.2008.2004640

This paper explores the possibilities of using monocular simultaneous localization and mapping (SLAM) algorithms in systems with more than one camera. The idea is to combine in a single system the advantages of both monocular vision (bearings-only, infinite range observations but no 3-D instantaneous information) and stereovision (3-D information up to a limited range). Such a system should be able to instantaneously map nearby objects while still considering the bearing information provided by the observation of remote ones. We do this by considering each camera as an independent sensor rather than the entire set as a monolithic supersensor. The visual data are treated by monocular methods and fused by the SLAM filter. Several advantages naturally arise as interesting possibilities, such as the desynchronization of the firing of the sensors, the use of several unequal cameras, self-calibration, and cooperative SLAM with several independently moving cameras. We validate the approach with two different applications: a stereovision SLAM system with automatic self-calibration of the rig's main extrinsic parameters and a cooperative SLAM system with two independent free-moving cameras in an outdoor setting.