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Open AccessArticle

Pedestrian Dead Reckoning-Assisted Visual Inertial Odometry Integrity Monitoring

1
School of Informatics, Xiamen University, Xiamen 361005, China
2
School of Computing, Ulster University, Newtownabbey BT37 0QB, UK
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(24), 5577; https://doi.org/10.3390/s19245577
Received: 5 November 2019 / Revised: 11 December 2019 / Accepted: 13 December 2019 / Published: 17 December 2019
(This article belongs to the Section Internet of Things)
Visual inertial odometers (VIOs) have received increasing attention in the area of indoor positioning due to the universality and convenience of the camera. However, the visual observation of VIO is more susceptible to the environment, and the error of observation affects the final positioning accuracy. To address this issue, we analyzed the causes of visual observation error that occur under different scenarios and their impact on positioning accuracy. We propose a new method of using the short-time reliability of pedestrian dead reckoning (PDR) to aid in visual integrity monitoring and to reduce positioning error. The proposed method selects optimized positioning by automatically switching between outputs from VIO and PDR. Experiments were carried out to test and evaluate the proposed PDR-assisted visual integrity monitoring. The sensor suite of experiments consisted of a stereo camera and an inertial measurement unit (IMU). Results were analyzed in detailed and indicated that the proposed system performs better for indoor positioning within an environment that contains low illumination, little background texture information, or few moving objects. View Full-Text
Keywords: visual-inertial odometer; pedestrian dead reckoning; autonomous integrity monitoring visual-inertial odometer; pedestrian dead reckoning; autonomous integrity monitoring
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MDPI and ACS Style

Wang, Y.; Peng, A.; Lin, Z.; Zheng, L.; Zheng, H. Pedestrian Dead Reckoning-Assisted Visual Inertial Odometry Integrity Monitoring. Sensors 2019, 19, 5577.

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