Abstract

Abstract. Annually, the extreme climate and special geological environments lead to frequent natural disasters, e.g., earthquakes, floods, etc. The disasters often bring serious casualties and enormous economic losses. Post-disaster surveying is very important for disaster relief and assessment. As the Unmanned Aerial Vehicle (UAV) remote sensing with the advantage of high efficiency, high precision, high flexibility, and low cost, it is widely used in emergency surveying in recent years. As the UAVs used in emergency surveying cannot stop and wait for the happening of the disaster, when the disaster happens the UAVs usually are working at everywhere. In order to improve the emergency surveying efficiency, it is needed to track the UAVs and assign the emergency surveying task for each selected UAV. Therefore, a UAV tracking and scheduling method for post-disaster survey is presented in this paper. In this method, Global Positioning System (GPS), and GSM network are used to track the UAVs; an emergency tracking UAV information database is built in advance by registration, the database at least includes the following information, e.g., the ID of the UAVs, the communication number of the UAVs; when catastrophe happens, the real time location of all UAVs in the database will be gotten using emergency tracking method at first, then the traffic cost time for all UAVs to the disaster region will be calculated based on the UAVs’ the real time location and the road network using the nearest services analysis algorithm; the disaster region is subdivided to several emergency surveying regions based on DEM, area, and the population distribution map; the emergency surveying regions are assigned to the appropriated UAV according to shortest cost time rule. The UAVs tracking and scheduling prototype is implemented using SQLServer2008, ArcEnginge 10.1 SDK, Visual Studio 2010 C#, Android, SMS Modem, and Google Maps API.

Highlights

  • The extreme climate and special geological environments lead to frequent natural disasters, including earthquakes, floods, etc., and often result in serious casualties and enormous economic losses

  • O’Rourke put forward the vehicle routing problem (VRP) model (O’Rourke, 2001); Secrest proposed multiple traveling salesman problem (MTSP) model (Secrest, 2001); Alighanbari (Alighanbari, 2004) presented mixed integer linear programming (MILP) model; Ye proposed multi-Unmanned Aerial Vehicle (UAV) task allocation formal model (Ye, 2005); Li established a single task dynamic programming model based on event-driven principle(Li, 2008); Zhang constructed the mathematical model of task assignment problem by considering the decision variables and constraint s(Zhang, 2009), etc

  • Su used division of labour mechanism of ant colony algorithm to solve CMTAP, and, designed the structure solution strategy based on competency assessment, state transition rules and the task cost according to the characteristics of collaborative task allocation (Su, 2008)

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Summary

INTRODUCTION

The extreme climate and special geological environments lead to frequent natural disasters, including earthquakes, floods, etc., and often result in serious casualties and enormous economic losses. The postdisaster survey and assessment is a significant technical work to reduce losses from natural disasters. Compared with conventional airborne or satellite remote sensing technology for disaster assessment, the Unmanned Aerial Vehicle (UAV) remote sensing means can improve the assessment work with advantages of its high precision, high flexibility, low cost, high efficiency and multi-angle imaging. Since 1990, UAV remote sensing technology has gradually taken active effect in data obtaining, geological disaster monitoring, rescuing and the loss assessment. Yu studied a dynamic resource scheduling algorithm based on genetic algorithm (Yu, 2004). Stutzle studied the multiple UAVs scheduling algorithm based on particle swarm optimization (PSO) (Stutzle, 1997), etc. An effective approach of UAVs tracking, scheduling and mission planning is studied in this paper.

UAV Tracking
UAV TASK PLANNING
UAV Scheduling
EXPERIMENTAL SOFTWARE
CONCLUSION
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