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ZJUS-A
Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering)  2006, Vol. 7 Issue (6): 937-944    DOI: 10.1631/jzus.2006.A0937
Electrical & Electronics Engineering     
A novel method for mobile robot simultaneous localization and mapping
LI Mao-hai, HONG Bing-rong, LUO Rong-hua, WEI Zhen-hua
School of Computer Science, Harbin Institute of Technology, Harbin 150001, China
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Abstract  A novel mobile robot simultaneous localization and mapping (SLAM) method is implemented by using the Rao-Blackwellized particle filter (RBPF) for monocular vision-based autonomous robot in unknown indoor environment. The particle filter combined with unscented Kalman filter (UKF) for extending the path posterior by sampling new poses integrating the current observation. Landmark position estimation and update is implemented through UKF. Furthermore, the number of resampling steps is determined adaptively, which greatly reduces the particle depletion problem. Monocular CCD camera mounted on the robot tracks the 3D natural point landmarks structured with matching image feature pairs extracted through Scale Invariant Feature Transform (SIFT). The matching for multi-dimension SIFT features which are highly distinctive due to a special descriptor is implemented with a KD-Tree. Experiments on the robot Pioneer3 showed that our method is very precise and stable.

Key words： Mobile robot      Rao-Blackwellized particle filter (RBPF)      Monocular vision      Simultaneous localization and mapping (SLAM)     
Received: 25 October 2005     
CLC:  TP24  
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LI Mao-hai
HONG Bing-rong
LUO Rong-hua
WEI Zhen-hua
Cite this article:

LI Mao-hai, HONG Bing-rong, LUO Rong-hua, WEI Zhen-hua. A novel method for mobile robot simultaneous localization and mapping. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2006, 7(6): 937-944.

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http://www.zjujournals.com/xueshu/zjus-a/10.1631/jzus.2006.A0937     OR     http://www.zjujournals.com/xueshu/zjus-a/Y2006/V7/I6/937

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