NDLI: Vision-based unscented FastSLAM for mobile robot

Content Provider	IEEE Xplore Digital Library
Author	Chunxin Qiu Xiaorui Zhu Xiaobing Zhao
Copyright Year	2012
Description	Author affiliation: Harbin Institute of Technology Shenzhen Graduate School, Guangdong 518055, China (Xiaorui Zhu)
Abstract	This paper presents a vision-based Unscented FastSLAM (UFastSLAM) algorithm combing the Rao-Blackwellized particle filter and Unscented Kalman filte(UKF). The landmarks are detected by a binocular vision to integrate localization and mapping. Since such binocular vision system generally inherits larger measurement errors, it is suitable to adopt Unscented FastSLAM to improve the performance of localization and mapping. Unscented FastSLAM takes advantage of UKF instead of the linear approximations of the nonlinear function where the effective number of particles is used as the criteria to reduce the particle degeneration. Simulations and experiments are carried out to demonstrate that the Unscented FastSLAM algorithm can achieve much better performance in the vision-based system than FastSLAM2.0 algorithm on the accuracy and robustness.
Starting Page	3758
Ending Page	3763
File Size	181610
Page Count	6
File Format	PDF
ISBN	9781467313971
e-ISBN	9781467313988
DOI	10.1109/WCICA.2012.6359099
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robot kinematics Simultaneous localization and mapping Trajectory Estimation Mobile robots FastSLAM Mobile robot Binocular vision UKF
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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