Abstract
In this paper, we consider the problem of mobile robot indoor position estimation using only visual information from a single camera. A camera which has a fish-eye lens is mounted on the top of the mobile robot and pointed to the ceiling. At the beginning of the visual positioning, we assume that we know the initial orientation and position of the mobile robot. Through the key point extraction, non-ceiling key point removal, key point calibration, ellipsoid construction and so on; the robot position and orientation can be determined after a short time moving.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Yuen, D.C.K., MacDonald, B.A.: Vision-Based Localization Algorithm Based on Landmark Matching, Triangulation, Reconstruction, and Comparison. IEEE Transactions on Robotics 21(2), 217–226 (2005)
Kitanov, A.: Mobile robot self-localization in complex indoor environments using monocular vision and 3D model
Koenig, A., Kessler, J., Gross, H.-M.: A Graph Matching Technique for an Appearance-based, visual SLAM-Approach using Rao-Blackwellized Particle Filters. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1576–1581 (2008)
Chen, K.-C., Tsai, W.-H.: Vision-Based Autonomous Vehicle Guidance for Indoor Security Patrolling by a SIFT-Based Vehicle-Localization Technique. IEEE Transactions on Vehicular Technology 59(7) (2010)
Xu, D., Han, L., Tan, M., Li, Y.F.: Ceiling-Based Visual Positioning for an Indoor Mobile Robot With Monocular Vision. IEEE Transactions on Industrial Electronics 56(5) (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Xiong, X., Choi, BJ. (2011). Relative Self-Localization Base on Fish-Eye Lenses and SIFT Algorithm for Indoor Mobile Robot. In: Kim, Th., Adeli, H., Robles, R.J., Balitanas, M. (eds) Information Security and Assurance. ISA 2011. Communications in Computer and Information Science, vol 200. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23141-4_41
Download citation
DOI: https://doi.org/10.1007/978-3-642-23141-4_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23140-7
Online ISBN: 978-3-642-23141-4
eBook Packages: Computer ScienceComputer Science (R0)