Abstract
The efficient accomplishment of missions can often be enhanced by the simultaneous operation of multiple unmanned aerial vehicles (UAVs). Easily scalable control algorithms are crucial for the implementation of such operational concept. One promising practical option is swarm intelligence, which is based on a behavioral model and boasts of characteristics such as flexibility, robustness, decentralized control, and self-organization. In this paper, a neural net controller that evolved via evolutionary robotics is applied to the control of multiple UAVs with the mission to search a bound area as thoroughly as possible. By applying incremental evolution techniques, a neural net controller that minimizes energy consumption without sacrificing performance in area coverage and collision avoidance can be developed. A much higher survival rate of UAVs can be achieved by applying a three-dimensional (3-D) maneuver for collision avoidance with an efficient algorithm for minimizing fuel consumption by suppressing excessive altitude maneuver. Numerical demonstrations are shown to validate the effectiveness of the proposed 3-D area search algorithm with minimum altitude maneuver.
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Recommended by Associate Editor Sangyoon Lee
Soo-Hun Oh received his B.S. and M.S. degrees in Aerospace Engineering from Seoul National University in 1988 and 1990, respectively. He received his Ph.D degree in Aerospace Engineering from Chungnam National University in 2010. His research interests include control of multiple UAVs, evolutionary robotics, and swarm robotics.
Jinyoung Suk received his Ph.D degree from Seoul National University. He joined the Department of Aerospace Engineering of the Chungnam National University in 2001. His research interests include UAVs, flight dynamics, and flight control.
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Oh, SH., Suk, J. Evolutionary controller design for area search using multiple UAVs with minimum altitude maneuver. J Mech Sci Technol 27, 541–548 (2013). https://doi.org/10.1007/s12206-012-1238-1
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DOI: https://doi.org/10.1007/s12206-012-1238-1