Research and development of SLAM back-end optimization based on graph optimization

Zhang Honghua
Liu Xuan
Chen Fuhao
Li Wenbin
Zhang Jianhua
School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China

Abstract

Simultaneous localization and mapping(SLAM) become a research hotspot in robot positioning and navigation. This paper elaborated the SLAM back-end optimization framework based on graph optimization from three aspects: optimization model, optimization algorithm and evaluation of results. In the aspect of modeling, this paper analyzed the modeling method based on dynamic Bayesian network, the modeling method based on factor graph and the modeling method based on Markov graph. In addition, it discussed the methods of back-end optimization, that is, least squares optimization method, relaxation optimization method, stochastic gradient descent optimization method and manifold optimization method. In the evaluation of the results, it described the evaluation of the results using χ2 error and MSE error. Finally, it made a prospect on the development of SLAM based on the current research hotspots.

Foundation Support

河北省杰出青年科学基金资助项目(F2017202062)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.12.0842
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 1
Section: Survey
Pages: 11-17
Serial Number: 1001-3695(2019)01-003-0011-07

Publish History

[2019-01-05] Printed Article

Cite This Article

张洪华, 刘璇, 陈付豪, 等. 基于图优化的SLAM后端优化研究与发展 [J]. 计算机应用研究, 2019, 36 (1): 11-17. (Zhang Honghua, Liu Xuan, Chen Fuhao, et al. Research and development of SLAM back-end optimization based on graph optimization [J]. Application Research of Computers, 2019, 36 (1): 11-17. )

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  • Application Research of Computers Monthly Journal
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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