Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICCA.2013.6564992
Title: Mission planning of autonomous UAVs for urban surveillance with evolutionary algorithms
Authors: Geng, L.
Zhang, Y.F. 
Wang, J.J.
Fuh, J.Y.H. 
Teo, S.H.
Issue Date: 2013
Source: Geng, L.,Zhang, Y.F.,Wang, J.J.,Fuh, J.Y.H.,Teo, S.H. (2013). Mission planning of autonomous UAVs for urban surveillance with evolutionary algorithms. IEEE International Conference on Control and Automation, ICCA : 828-833. ScholarBank@NUS Repository. https://doi.org/10.1109/ICCA.2013.6564992
Abstract: In this paper, a mission planning system is presented that generates mission plans for a group of unmanned aerial vehicles (UAVs) to provide continuous surveillance over an urban area. Given the information of terrain and buildings in the target area, a two-stage approach is employed to solve the problem. In the first stage, a set of camera locations called the vantage set is generated that provides complete coverage of the target area. In the second stage, one or several UAVs are determined to collectively share the vantage set and their individual paths are generated to carry out the continuous surveillance duty. In both stages, evolutionary algorithms (genetic algorithm for vantage set generation and ant colony system for UAV/path planning) are used to search for the optimal solution. During the search, constraints such as the flying capabilities of UAVs and collision avoidance are imposed to guarantee the feasibility of the final result. © 2013 IEEE.
Source Title: IEEE International Conference on Control and Automation, ICCA
URI: http://scholarbank.nus.edu.sg/handle/10635/73617
ISBN: 9781467347075
ISSN: 19483449
DOI: 10.1109/ICCA.2013.6564992
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