[1]ZHANG Yi,SHA Jiansong.Visual-SLAM for mobile robot based on graph optimization[J].CAAI Transactions on Intelligent Systems,2018,13(2):290-295.[doi:10.11992/tis.201612004]
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Visual-SLAM for mobile robot based on graph optimization

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 13 Number of periods: 2018 2 Page number: 290-295 Column: 学术论文—智能系统 Public date: 2018-04-15
Title:
Visual-SLAM for mobile robot based on graph optimization
Author(s):
ZHANG Yi;  SHA Jiansong
Laboratory of Intelligent System and Robotics, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
Keywords:
RGB-D; mobile robot; graph optimization; SLAM; pose and point cloud optimization
CLC:
TP24
DOI:
10.11992/tis.201612004
Abstract:
In the present research on the visual SLAM (Simultaneous Localization and Mapping)of mobile robot, some defects as inferior real-timeness, low accuracy and hard to densified mapping exist, therefore, the paper proposed a real-time SLAM algorithm based on RGB-D data. In the front-end processing of the algorithm, the ORB feature detection with better robustness and real-timeness was adopted. RANSAC algorithm was utilized to get rid of the possible mismatch points and complete the initial match. For the obtained inner point, PNP solution was carried out for using as the increment estimate of the adjacent pose of robot. In the rear-end optimization, a nonlinear optimization method obeying image optimization thought was used for optimizing the pose of a moving robot. In addition, in combination with the closed-loop detection mechanism, a point cloud optimization algorithm was proposed to suppress the cumulative error of the system and further improve the accuracy of pose and point cloud. The experimental results show that the proposed method can reconstruct the dense 3D environment model quickly and accurately.
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