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4 October 2018 A robust localization approach using multi-sensor fusion
Weijian Hu, Kaiwei Wang, Hao Chen
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Proceedings Volume 10799, Emerging Imaging and Sensing Technologies for Security and Defence III; and Unmanned Sensors, Systems, and Countermeasures; 107990U (2018) https://doi.org/10.1117/12.2325521
Event: SPIE Security + Defence, 2018, Berlin, Germany
Abstract
In recent years, with development of computer vision and robotics, a wide variety of localization approaches have been proposed. However, it is still challenging to design a localization algorithm that performs well in both indoor and outdoor environment. In this paper, an algorithm that fuses camera, IMU, GPS, as well as digital compass is proposed to solve this problem. Our algorithm includes two phases: (1) the monocular RGB camera and IMU are fused together as a VIO that estimates the approximate orientation and position; (2) the absolute position and orientation measured by GPS and digital compass are merged with the position and orientation estimated in first phase to get a refined result in the world coordinate. A bag-of-word based algorithm is utilized to realize loop detection and relocalization. We also built a prototype and did two experiments to evaluate the effectiveness and robustness of the localization algorithm in both indoors and outdoors environment.
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Weijian Hu, Kaiwei Wang, and Hao Chen "A robust localization approach using multi-sensor fusion", Proc. SPIE 10799, Emerging Imaging and Sensing Technologies for Security and Defence III; and Unmanned Sensors, Systems, and Countermeasures, 107990U (4 October 2018); https://doi.org/10.1117/12.2325521
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KEYWORDS
Global Positioning System
Cameras
Particle filters
Unmanned aerial vehicles
Data fusion
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