Cooperative Multiple Task Assignment of Heterogeneous UAVs Using a Modified Genetic Algorithm with Multi-type-gene Chrom
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Cooperative Multiple Task Assignment of Heterogeneous UAVs Using a Modified Genetic Algorithm with Multi-type-gene Chromosome Encoding Strategy Fang Ye1 · Jie Chen1 · Yuan Tian1 · Tao Jiang1 Received: 21 April 2019 / Accepted: 26 February 2020 © Springer Nature B.V. 2020
Abstract The cooperative multiple task assignment problem (CMTAP) of heterogeneous fixed-wing unmanned aerial vehicles (UAVs) performing the Suppression of Enemy Air Defense (SEAD) mission against multiple ground stationary targets is studied in this paper. The CMTAP is a NP-hard combinatorial optimization problem, which faces many challenges like problem scale, heterogeneity of UAVs (different capability and maneuverability), task coupling and task precedence constraints. To address this issue, we proposed a modified genetic algorithm (GA) with multi-type-gene chromosome encoding strategy. Firstly, the multi-type-gene encoding scheme is raised to generate feasible chromosomes that satisfy the UAV capability, task coupling and task precedence constraints. Then, Dubins car model is adopted to calculate the mission execution time (objective function of CMTAP model) of each chromosome, and make each chromosome conform to the UAV maneuverability constraint. To balance the searching ability of algorithm and the diversity of population, we raise the modified crossover operator and multiple mutation operators according to the multi-type-gene chromosome encoding. The simulation results demonstrate that the modified GA has better optimization performance compared with random search method, ant colony optimization method and particle search optimization method. Keywords Unmanned aerial vehicles · Cooperative task assignment · Genetic algorithm · Multi-type-gene chromosome encoding · Dubins car model
1 Introduction Unmanned aerial vehicle (UAV) has the advantages of low cost, zero casualty, strong mobility and low detectability, which is capable of performing boring, harsh, dangerous and hidden tasks in complex battlefield [1, 2]. Due to
Yuan Tian
[email protected] Fang Ye [email protected] Jie Chen [email protected] Tao Jiang jiangtao [email protected] 1
College of Information and Communication Engineering, Harbin Engineering University, Harbin, 150001, China
limit capacity, single UAV cannot realize multi-dimensional and extensive coverage of mission area. Thus, the development of multi-UAV cooperation is essential to improve the efficiency of mission completion [3]. This paper concentrates on cooperative task assignment that allocates multiple heterogeneous fix-wing UAVs to perform Suppression of Enemy Air Defense (SEAD) mission on multiple ground stationary targets. The cooperative multiple task assignment problem (CMTAP) in this paper has two characteristics. Firstly, UAV team is composed of heterogeneous fix-wing UAVs, including the surveillance UAV, combat UAV and munition UAV. The heterogeneity of UAVs reflects on different capability (ability to perform certain tasks, e.g., munition UAV can only execute attack task) and different maneuverabili
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