This paper is aimed at developing a swarm unmanned aerial vehicle (UAV) network for motion in free space controlled by an algorithm depending on axis-aligned minimum bounding space, and a collision is avoided by the use of a collision-free trajectory planning algorithm depending on the position of the UAVs by implementing the optimization technique named particle swarm optimization (PSO) algorithm for intelligent features. PSO is an algorithm where each quad has its own information and also combined information of the environment due to their interaction. Wireless network was used in swarm UAVs implementation to connect to a server processor that analyses the PSO equation and controls the quadcopters. This experiment includes 3 UAVs and one object as target (Stationary and Moving).
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|Journal||Data powered by TypesetProceedings of the International Conference on Soft Computing Systems Advances in Intelligent Systems and Computing|
|Publisher||Data powered by TypesetSpringer India|