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Sequential Covariance-weighted Quasiconvex solution to Mapping in Visual SLAM

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Makale Dosyası (398.1Kb)

Date

2015-03

Author

Hafez, A. H. Abdul

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Citation

Abdul, H. A. H. (January 01, 2015). Sequential covariance-weighted quasiconvex solution to mapping in visual SLAM. Control Engineering and Applied Informatics, 17, 1, 61-69.

Abstract

This paper presents a new sequential real time algorithm that solves the mapping problem in Visual SLAM. The considered problem is a particular example from the triangulation problem, that has direct applications to robotic vision domain. In other words, the problem is handled as 3D estimate problem. The estimation process is formulated as a minimization problem of quasiconvex objective function. The minimization process is realized using the well-known bisection algorithm. The bisection algorithm runs sequentially solving one convex feasibility problem in each iteration, trying to reduce the bound on the 3D estimate. New image measurements arrive after every new iteration, new convex visibility problem is solved, and the bounds on the 3D estimates are updated. These steps are repeated till convergence. We conducted a set of experiments to show the applicability to the general reconstruction (triangulation) problem as well as the application to mapping Visual SLAM.

Source

CONTROL ENGINEERING AND APPLIED INFORMATICS

Volume

17

Issue

1

URI

https://hdl.handle.net/20.500.11782/835

Collections

  • MF - BM Makale Koleksiyonu [51]
  • Scopus İndeksli Yayınlar Koleksiyonu [588]
  • WoS İndeksli Yayınlar Koleksiyonu [549]



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