Visual Data Driven Approach for Metric Localization in Substation

Wu, Hua; Wu, Yanxiong; Liu, Changan; Yang, Guohui

doi:10.1049/cje.2015.10.022

Cited by 9 publications

(2 citation statements)

References 25 publications

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“…The BRIEF [20] and ORB [21] features are also used to create bag of words to speed up calculations. Latif et al [22] uses bag of words to detect the loop and Hua et al [23] adds multi-view geometry information to improve the performance in high similarity environments. Dominik and Giorgio [24] proposes a dynamic self-adaption decision tree to improve the speed of data association, which can be regarded as a heuristic search method.…”

Section: Data Associationmentioning

confidence: 99%

Non-Uniform Network Mapping and Localization

2020

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The purpose of this paper is to establish a new simultaneous localization and mapping (SLAM) framework, which can make better use of the spatial structure of the environment, to improve the robustness and reliability of the system. To locate, a good map should be not only a representation of the real environment, but also a highly compressed and intelligently organized geography information of the environment. Furthermore, the map structure should be stable and robust to inevitable errors. Inspired by human positioning ability, we developed a non-uniform network mapping and localization algorithm (NU-SLAM) based on the complex network theory. Landmarks are classified and sparsely connected according to their localization ability. Therefore, data association and information transmission can be carried out hierarchically with low computational cost and robustness to data association errors. In this paper, a new visual to the mapping and localization problem is proposed. Simulation results show that the algorithm can achieve good results.

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Section: Data Associationmentioning

confidence: 99%

Non-Uniform Network Mapping and Localization

2020

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“…To apply SLAM methods to real-world applications [28] , the estimation accuracy and robustness remain challenging. In real-world applications, customization of the algorithm with the nature and constraints of the problem is important.…”

Section: Mobility Intelligencementioning

confidence: 99%