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Scientific Programming
Volume 2017, Article ID 7136702, 10 pages
Research Article

Underwater Matching Correction Navigation Based on Geometric Features Using Sonar Point Cloud Data

1Robotics Institute, Beijing University of Aeronautics and Astronautics, XueYuan Road No. 37, HaiDian District, Beijing 100191, China
2State Key Lab of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, HaiDian District, Beijing 100083, China

Correspondence should be addressed to Mingjie Dong; nc.ude.aaub@jmgnod

Received 11 September 2016; Accepted 1 December 2016; Published 4 January 2017

Academic Editor: Wenbing Zhao

Copyright © 2017 Mingjie Dong et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In order to localize the Remotely Operated Vehicle (ROV) accurately in the reactor pool of the nuclear power plant, an underwater matching correction navigation algorithm based on geometric features using sonar point cloud data is proposed. At first, an Extended Kalman Filter (EKF) is used to compensate the motion induced distortion after the preprocessing of the sonar point cloud data. Then, the adjacent scanning point cloud data are fitted to be four different straight lines using Hough Transform and least square method. After that, the adjacent straight line is modified based on geometric features to get a standard rectangle. Since the working environment of the ROV is a rectangular shape with all dimensions known, it is used as a priori map. The matching rectangle is then used to compare with the a priori map to calculate the accurate position and orientation of the ROV. The obtained result is then applied as the measurement for the second EKF to obtain better localization accuracy. Experiments have been conducted in man-made water tank which is similar to the reactor pool of the nuclear power plant, and the results successfully verify the effectiveness of the proposed algorithm.