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Extension of an iterative closest point algorithm for simultaneous localization and mapping in corridor environments

[+] Author Affiliations
Haosong Yue, Weihai Chen, Xingming Wu, Jianhua Wang

Beihang University, School of Automation Science and Electrical Engineering, Xueyuan Road, Haidian District, Beijing 100191, China

J. Electron. Imaging. 25(2), 023015 (Apr 05, 2016). doi:10.1117/1.JEI.25.2.023015
History: Received September 25, 2015; Accepted March 2, 2016
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Abstract.  Three-dimensional (3-D) simultaneous localization and mapping (SLAM) is a crucial technique for intelligent robots to navigate autonomously and execute complex tasks. It can also be applied to shape measurement, reverse engineering, and many other scientific or engineering fields. A widespread SLAM algorithm, named KinectFusion, performs well in environments with complex shapes. However, it cannot handle translation uncertainties well in highly structured scenes. This paper improves the KinectFusion algorithm and makes it competent in both structured and unstructured environments. 3-D line features are first extracted according to both color and depth data captured by Kinect sensor. Then the lines in the current data frame are matched with the lines extracted from the entire constructed world model. Finally, we fuse the distance errors of these line-pairs into the standard KinectFusion framework and estimate sensor poses using an iterative closest point-based algorithm. Comparative experiments with the KinectFusion algorithm and one state-of-the-art method in a corridor scene have been done. The experimental results demonstrate that after our improvement, the KinectFusion algorithm can also be applied to structured environments and has higher accuracy. Experiments on two open access datasets further validated our improvements.

© 2016 SPIE and IS&T

Topics

Sensors ; Robots

Citation

Haosong Yue ; Weihai Chen ; Xingming Wu and Jianhua Wang
"Extension of an iterative closest point algorithm for simultaneous localization and mapping in corridor environments", J. Electron. Imaging. 25(2), 023015 (Apr 05, 2016). ; http://dx.doi.org/10.1117/1.JEI.25.2.023015


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