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ISPRS Int. J. Geo-Inf. 2016, 5(10), 184; doi:10.3390/ijgi5100184

Unmanned Aerial Vehicle Route Planning in the Presence of a Threat Environment Based on a Virtual Globe Platform

1
Shenzhen Graduate School, Peking University, Shenzhen 518055, China
2
Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong
*
Author to whom correspondence should be addressed.
Academic Editor: Wolfgang Kainz
Received: 5 July 2016 / Revised: 27 September 2016 / Accepted: 28 September 2016 / Published: 10 October 2016

Abstract

Route planning is a key technology for an unmanned aerial vehicle (UAV) to fly reliably and safely in the presence of a threat environment. Existing route planning methods are mainly based on the simulation scene, whereas approaches based on the virtual globe platform have rarely been reported. In this paper, a new planning space for the virtual globe and the planner is proposed and a common threat model is constructed for threats including a no-fly zone, hazardous weather, radar coverage area, missile killing zone and dynamic threats. Additionally, an improved ant colony optimization (ACO) algorithm is developed to enhance route planning efficiency and terrain masking ability. Our route planning methods are optimized on the virtual globe platform for practicability. A route planning system and six types of planners were developed and implemented on the virtual globe platform. Finally, our evaluation results demonstrate that our optimum planner has better performance in terms of fuel consumption, terrain masking, and risk avoidance. Experiments also demonstrate that the method and system described in this paper can be used to perform global route planning and mission operations. View Full-Text
Keywords: unmanned aerial vehicle; route planning; virtual globe; ant colony optimization; 3D environments unmanned aerial vehicle; route planning; virtual globe; ant colony optimization; 3D environments
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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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MDPI and ACS Style

Zhang, M.; Su, C.; Liu, Y.; Hu, M.; Zhu, Y. Unmanned Aerial Vehicle Route Planning in the Presence of a Threat Environment Based on a Virtual Globe Platform. ISPRS Int. J. Geo-Inf. 2016, 5, 184.

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