Overview of the research on state-of-the-art measurement sensors for UAV navigation

The skyrocketing development of the civilian drones' market, which follows the military solutions, results in boosting research on UAV avionics systems. The research includes a development of classic navigation and control as well as innovative methods that require e.g. infrared and visible light cameras, laser or magnetic field sensors. In this paper, we focus on the research on UAV's navigation and control systems, state-of-the-art measurement sensors involved in classic systems as well as the research on innovative methods of navigation and control.

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[41]  Jonghyuk Kim,et al.  Integrated navigation system using camera and gimbaled laser scanner for indoor and outdoor autonomous flight of UAVs , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[42]  Seong Yun Cho,et al.  IM-filter for INS/GPS-integrated navigation system containing low-cost gyros , 2014, IEEE Transactions on Aerospace and Electronic Systems.

[43]  Mark R. Morelande,et al.  Tightly coupled MEMS based INS/GNSS performance evaluation during extended GNSS outages , 2013 .

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[45]  Eric N. Johnson,et al.  Performance of a Monocular Vision-aided Inertial Navigation System for a Small UAV , 2013 .

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[47]  Feng Lin,et al.  A stereo and rotating laser framework for UAV navigation in GPS denied environment , 2016, IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society.

[48]  Roberto Sabatini,et al.  Carrier-phase GNSS Attitude Determination and Control for Small Unmanned Aerial Vehicle Applications , 2013 .

[49]  Giancarmine Fasano,et al.  Cooperative UAV navigation based on distributed multi-antenna GNSS, vision, and MEMS sensors , 2015, 2015 International Conference on Unmanned Aircraft Systems (ICUAS).

[50]  Yihe Li,et al.  GPS /INS Tightly Coupled Integration Based on Adaptive Robust Kalman Filter , 2011 .

[51]  Mohammad A. Jaradat,et al.  Optimization of Intelligent Approach for Low-Cost INS/GPS Navigation System , 2014, J. Intell. Robotic Syst..