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Sensors 2017, 17(8), 1842;

A Heterogeneous Sensing System-Based Method for Unmanned Aerial Vehicle Indoor Positioning

Guangdong Provincial Key Laboratory of Robotics and Intelligent System, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430000, China
School of Mechanical Engineering and Automation, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518055, China
Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong 999077, China
This paper is an extended version of an earlier conference paper: Li, K.; Wang, C.; Huang, S.; Liang, G.; Wu, X.; Liao, Y. Self-positioning for UAV indoor navigation based on 3D laser scanner, UWB and INS. In Proceedings of the IEEE International Conference on Information and Automation (ICIA), Ningbo, China, 31 July–4 August 2016.
Author to whom correspondence should be addressed.
Received: 23 May 2017 / Revised: 24 July 2017 / Accepted: 25 July 2017 / Published: 10 August 2017
(This article belongs to the Section Physical Sensors)
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The indoor environment has brought new challenges for micro Unmanned Aerial Vehicles (UAVs) in terms of their being able to execute tasks with high positioning accuracy. Conventional positioning methods based on GPS are unreliable, although certain circumstances of limited space make it possible to apply new technologies. In this paper, we propose a novel indoor self-positioning system of UAV based on a heterogeneous sensing system, which integrates data from a structured light scanner, ultra-wideband (UWB), and an inertial navigation system (INS). We made the structured light scanner, which is composed of a low-cost structured light and camera, ourselves to improve the positioning accuracy at a specified area. We applied adaptive Kalman filtering to fuse the data from the INS and UWB while the vehicle was moving, as well as Gauss filtering to fuse the data from the UWB and the structured light scanner in a hovering state. The results of our simulations and experiments demonstrate that the proposed strategy significantly improves positioning accuracy in motion and also in the hovering state, as compared to using a single sensor. View Full-Text
Keywords: unmanned aerial vehicle; indoor positioning; heterogeneous sensing system; data fusion unmanned aerial vehicle; indoor positioning; heterogeneous sensing system; data fusion

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Wang, C.; Li, K.; Liang, G.; Chen, H.; Huang, S.; Wu, X. A Heterogeneous Sensing System-Based Method for Unmanned Aerial Vehicle Indoor Positioning. Sensors 2017, 17, 1842.

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