Journal of System Simulation
Abstract
Abstract: To reduce the accumulated pose error of robots during the three-dimensional simultaneous localization and mapping, a global optimization method is proposed to improve the positioning accuracy and the quality of the map. This method, which is based on the visual odometry of the frame and frame registration model, adds the pose-constraints by closed-loop detection based on image matching. Local loop is combined with random loop to improve the optimization efficiency. The general graph optimization algorithm is used to globally optimize the robot poses. A key-frame selection strategy is also proposed to decrease the consumption of the computing resources and memory footprint. The experiment results show that this method can reduce the root mean square error to only 8.7mm with a 3.96 m path and generate 3D map of indoor scenes accurately.
Recommended Citation
Hu, Lingyan; Lu, Cao; Xiong, Pengwen; Yong, Xin; and Xie, Zekun
(2020)
"3D Simultaneous Localization and Mapping Based on RGB-D Images,"
Journal of System Simulation: Vol. 29:
Iss.
11, Article 33.
DOI: 10.16182/j.issn1004731x.joss.201711033
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol29/iss11/33
First Page
2840
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.201711033
Last Page
2846
CLC
TP391.41
Recommended Citation
Hu Lingyan, Cao Lu, Xiong Pengwen, Xin Yong, Xie Zekun. 3D Simultaneous Localization and Mapping Based on RGB-D Images[J]. Journal of System Simulation, 2017, 29(11): 2840-2846.
DOI
10.16182/j.issn1004731x.joss.201711033
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