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Sensors 2019, 19(2), 249; https://doi.org/10.3390/s19020249

A Robust Indoor Localization System Integrating Visual Localization Aided by CNN-Based Image Retrieval with Monte Carlo Localization

1,* , 1,2
and
1
1
School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China
2
State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing 100191, China
*
Author to whom correspondence should be addressed.
Received: 6 November 2018 / Revised: 21 December 2018 / Accepted: 7 January 2019 / Published: 10 January 2019
(This article belongs to the Section Physical Sensors)
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Abstract

This paper proposes a novel multi-sensor-based indoor global localization system integrating visual localization aided by CNN-based image retrieval with a probabilistic localization approach. The global localization system consists of three parts: coarse place recognition, fine localization and re-localization from kidnapping. Coarse place recognition exploits a monocular camera to realize the initial localization based on image retrieval, in which off-the-shelf features extracted from a pre-trained Convolutional Neural Network (CNN) are adopted to determine the candidate locations of the robot. In the fine localization, a laser range finder is equipped to estimate the accurate pose of a mobile robot by means of an adaptive Monte Carlo localization, in which the candidate locations obtained by image retrieval are considered as seeds for initial random sampling. Additionally, to address the problem of robot kidnapping, we present a closed-loop localization mechanism to monitor the state of the robot in real time and make adaptive adjustments when the robot is kidnapped. The closed-loop mechanism effectively exploits the correlation of image sequences to realize the re-localization based on Long-Short Term Memory (LSTM) network. Extensive experiments were conducted and the results indicate that the proposed method not only exhibits great improvement on accuracy and speed, but also can recover from localization failures compared to two conventional localization methods. View Full-Text
Keywords: indoor global localization; monocular camera; laser range finder; image retrieval; convolutional neural network; kidnapping indoor global localization; monocular camera; laser range finder; image retrieval; convolutional neural network; kidnapping
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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 (CC BY 4.0).
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Xu, S.; Chou, W.; Dong, H. A Robust Indoor Localization System Integrating Visual Localization Aided by CNN-Based Image Retrieval with Monte Carlo Localization. Sensors 2019, 19, 249.

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