Optimizing the flight trajectory unmanned aerial vehicles (UAVs) is always a popular optimization problem in computation intelligence field, which aims to search optimal flight path for avoiding detection and complementing some highly difficult missions in complex military environments. This paper mainly utilizes a recent proposed biology migration algorithm (BMA) inspired by the species migration mechanism for dealing with the UAV trajectory optimization problem. The main goal of the UAV model is to search feasible parameters including the flight angle, coordinates and distance for minimizing the flight price computed based on the threat and fuel costs. As one of swarm intelligence techniques, BMA has the characteristics of self-organization, fast convergence and self-adaption in the optimization process, So, it is able to find a safe flight route between the start point and target point while avoiding the dangerous regions and minimum cost. Simulation experiments show that BMA can generate promising and better results with respective to other compared algorithms.
|Number of pages||8|
|Journal||Journal of Physics: Conference Series|
|Publication status||Published - 28 Sept 2021|
|Event||2021 3rd International Conference on Artificial Intelligence and Computer Science, AICS 2021 - Beijing, China|
Duration: 29 Jul 2021 → 31 Jul 2021
Bibliographical noteFunding Information:
This work is supported by the National Natural Science Foundation of China under Grants 62006103 and 61872168, in part by the Jiangsu national science research of high education under Grand 20KJB110021.
- Biology migration algorithm
- Trajectory optimization
- Unmanned aerial vehicle