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Sensors 2016, 16(5), 666; doi:10.3390/s16050666

Enabling UAV Navigation with Sensor and Environmental Uncertainty in Cluttered and GPS-Denied Environments

Australian Research Centre for Aerospace Automation (ARCAA), Queensland University of Technology (QUT), 2 George St, Brisbane, QLD 4000, Australia
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Author to whom correspondence should be addressed.
Academic Editor: Assefa M. Melesse
Received: 21 December 2015 / Revised: 3 May 2016 / Accepted: 5 May 2016 / Published: 10 May 2016
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
View Full-Text   |   Download PDF [3190 KB, uploaded 10 May 2016]   |  

Abstract

Unmanned Aerial Vehicles (UAV) can navigate with low risk in obstacle-free environments using ground control stations that plan a series of GPS waypoints as a path to follow. This GPS waypoint navigation does however become dangerous in environments where the GPS signal is faulty or is only present in some places and when the airspace is filled with obstacles. UAV navigation then becomes challenging because the UAV uses other sensors, which in turn generate uncertainty about its localisation and motion systems, especially if the UAV is a low cost platform. Additional uncertainty affects the mission when the UAV goal location is only partially known and can only be discovered by exploring and detecting a target. This navigation problem is established in this research as a Partially-Observable Markov Decision Process (POMDP), so as to produce a policy that maps a set of motion commands to belief states and observations. The policy is calculated and updated on-line while flying with a newly-developed system for UAV Uncertainty-Based Navigation (UBNAV), to navigate in cluttered and GPS-denied environments using observations and executing motion commands instead of waypoints. Experimental results in both simulation and real flight tests show that the UAV finds a path on-line to a region where it can explore and detect a target without colliding with obstacles. UBNAV provides a new method and an enabling technology for scientists to implement and test UAV navigation missions with uncertainty where targets must be detected using on-line POMDP in real flight scenarios. View Full-Text
Keywords: unmanned aircraft; UAV target detection; Partially-Observable Markov Decision Process (POMDP); path planning; Robotic Operating System (ROS); uncertainty; robust navigation unmanned aircraft; UAV target detection; Partially-Observable Markov Decision Process (POMDP); path planning; Robotic Operating System (ROS); uncertainty; robust navigation
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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Vanegas, F.; Gonzalez, F. Enabling UAV Navigation with Sensor and Environmental Uncertainty in Cluttered and GPS-Denied Environments. Sensors 2016, 16, 666.

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