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Wind-energy based path planning for electric unmanned aerial vehicles using Markov Decision Processes

Al-Sabban, Wesam H., Gonzalez, Luis F., Smith, Ryan N., & Wyeth, Gordon F. (2012) Wind-energy based path planning for electric unmanned aerial vehicles using Markov Decision Processes. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, Hotel Tivoli Marina Vilamoura, Algarve.

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Abstract

Exploiting wind-energy is one possible way to ex- tend flight duration for Unmanned Arial Vehicles. Wind-energy can also be used to minimise energy consumption for a planned path. In this paper, we consider uncertain time-varying wind fields and plan a path through them. A Gaussian distribution is used to determine uncertainty in the Time-varying wind fields. We use Markov Decision Process to plan a path based upon the uncertainty of Gaussian distribution. Simulation results that compare the direct line of flight between start and target point and our planned path for energy consumption and time of travel are presented. The result is a robust path using the most visited cell while sampling the Gaussian distribution of the wind field in each cell.

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ID Code: 49811
Item Type: Conference Paper
Keywords: Path Planning, Markov Decision Process, Aerial Vehicle, Energy Efficient
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Adaptive Agents and Intelligent Robotics (080101)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100) > Aircraft Performance and Flight Control Systems (090104)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > Institutes > Institute for Future Environments
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2012 [please consult the author]
Copyright Statement: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.
Deposited On: 23 Apr 2012 09:14
Last Modified: 21 Jan 2014 23:40

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