A Novel Improved Probability-Guided RANSAC Algorithm for Robot 3D Map Building
Joint Authors
Xu, Tao
Jia, Songmin
Li, Xiuzhi
Wang, Ke
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-18, 18 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-04-11
Country of Publication
Egypt
No. of Pages
18
Main Subjects
Abstract EN
This paper presents a novel improved RANSAC algorithm based on probability and DS evidence theory to deal with the robust pose estimation in robot 3D map building.
In this proposed RANSAC algorithm, a parameter model is estimated by using a random sampling test set.
Based on this estimated model, all points are tested to evaluate the fitness of current parameter model and their probabilities are updated by using a total probability formula during the iterations.
The maximum size of inlier set containing the test point is taken into account to get a more reliable evaluation for test points by using DS evidence theory.
Furthermore, the theories of forgetting are utilized to filter out the unstable inliers and improve the stability of the proposed algorithm.
In order to boost a high performance, an inverse mapping sampling strategy is adopted based on the updated probabilities of points.
Both the simulations and real experimental results demonstrate the feasibility and effectiveness of the proposed algorithm.
American Psychological Association (APA)
Jia, Songmin& Wang, Ke& Li, Xiuzhi& Xu, Tao. 2016. A Novel Improved Probability-Guided RANSAC Algorithm for Robot 3D Map Building. Journal of Sensors،Vol. 2016, no. 2016, pp.1-18.
https://search.emarefa.net/detail/BIM-1110415
Modern Language Association (MLA)
Jia, Songmin…[et al.]. A Novel Improved Probability-Guided RANSAC Algorithm for Robot 3D Map Building. Journal of Sensors No. 2016 (2016), pp.1-18.
https://search.emarefa.net/detail/BIM-1110415
American Medical Association (AMA)
Jia, Songmin& Wang, Ke& Li, Xiuzhi& Xu, Tao. A Novel Improved Probability-Guided RANSAC Algorithm for Robot 3D Map Building. Journal of Sensors. 2016. Vol. 2016, no. 2016, pp.1-18.
https://search.emarefa.net/detail/BIM-1110415
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1110415