Sensors 2014, 14(4), 6317-6337; doi:10.3390/s140406317

Monocular SLAM for Autonomous Robots with Enhanced Features Initialization

1email, 2email and 1,* email
Received: 6 January 2014; in revised form: 19 March 2014 / Accepted: 26 March 2014 / Published: 2 April 2014
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Spain 2013)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: This work presents a variant approach to the monocular SLAM problem focused in exploiting the advantages of a human-robot interaction (HRI) framework. Based upon the delayed inverse-depth feature initialization SLAM (DI-D SLAM), a known monocular technique, several but crucial modifications are introduced taking advantage of data from a secondary monocular sensor, assuming that this second camera is worn by a human. The human explores an unknown environment with the robot, and when their fields of view coincide, the cameras are considered a pseudo-calibrated stereo rig to produce estimations for depth through parallax. These depth estimations are used to solve a related problem with DI-D monocular SLAM, namely, the requirement of a metric scale initialization through known artificial landmarks. The same process is used to improve the performance of the technique when introducing new landmarks into the map. The convenience of the approach taken to the stereo estimation, based on SURF features matching, is discussed. Experimental validation is provided through results from real data with results showing the improvements in terms of more features correctly initialized, with reduced uncertainty, thus reducing scale and orientation drift. Additional discussion in terms of how a real-time implementation could take advantage of this approach is provided.
Keywords: monocular SLAM; human-robot interaction; HRI; stereo matching; depth estimation
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MDPI and ACS Style

Guerra, E.; Munguia, R.; Grau, A. Monocular SLAM for Autonomous Robots with Enhanced Features Initialization. Sensors 2014, 14, 6317-6337.

AMA Style

Guerra E, Munguia R, Grau A. Monocular SLAM for Autonomous Robots with Enhanced Features Initialization. Sensors. 2014; 14(4):6317-6337.

Chicago/Turabian Style

Guerra, Edmundo; Munguia, Rodrigo; Grau, Antoni. 2014. "Monocular SLAM for Autonomous Robots with Enhanced Features Initialization." Sensors 14, no. 4: 6317-6337.

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