Abstract
The multi-unmanned aerial vehicle (UAV) task allocation method has shortcomings such as long flight distance and long algorithm initialization time. In response to these problems, this paper proposes a UAV task allocation method based on Swarm Intelligence Optimization Algorithm (SIOA). The algorithm first compares the relationship between the number of UAVs and mission points when UAV is performing a task, and then introduces the idea of gradient descent to reduce the flying distance of UAV. Experimental results show that the SIOA method can effectively reduce the initialization time, shorten search distance of the UAV and the time UAV complete the task, and effectively solve the problem of high algorithm complexity.
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Shi, J., Tan, L., Lian, X., Xu, T., Zhang, H. (2021). UAV Task Allocation Method Using Swarm Intelligence Optimization Algorithm. In: Cui, L., Xie, X. (eds) Wireless Sensor Networks. CWSN 2021. Communications in Computer and Information Science, vol 1509. Springer, Singapore. https://doi.org/10.1007/978-981-16-8174-5_3
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DOI: https://doi.org/10.1007/978-981-16-8174-5_3
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