Abstract
Most research regarding multi-target, multi-base, and multi-unmanned aerial vehicle (UAV) coordinated combat mission planning faces the problems of ignoring heterogeneous UAVs, as well as poor task allocation and trajectory planning coupling. To solve these problems, based on air maneuver combat mission backgrounds, the present paper provided a heterogeneous multi-UAV cooperative mission planning method in the complex three-dimensional (3D) mountain environment. In the present paper, based on the Life-cycle Swarm Optimization (LSO) algorithm, varying the number of individuals in the population was utilized to improve the algorithm and further combined with the Rapidly exploring Random Tree (RRT) algorithm to obtain an optimized path. Then, an improved algorithm was utilized for task allocation and trajectory optimization, and the number and speed of drones dispatched by each base were determined regarding time coordination. Finally, a simulation experiment was conducted. Numerical simulation results showed that the following algorithm was compared with the Particle Swarm Optimization (PSO) algorithm and the Whale Optimization Algorithm (WOA) when considering radar threats and solid obstacle areas. This has good approximation and high convergence accuracy, and it was effectively utilized in the planning of UAV collaborative missions in 3D complex terrain environments.
Highlights
Unmanned aerial vehicle (UAV) is an organic combination of information equipment and military equipment
DESCRIPTION OF THE SIMULATION SCENARIO Aiming at the problem of multi-UAV collaborative mission planning, the present study introduced a hierarchical optimization strategy into the drone collaborative mission planning, and it utilized an Improved Life-cycle Swarm Optimization (ILSO) algorithm to solve the
The ILSO algorithm was combined with the Rapidly exploring Random Tree (RRT) algorithm to initialize the path; the revenue function was established at the task allocation level; and the ILAO algorithm was utilized at the trajectory re-optimization level
Summary
Unmanned aerial vehicle (UAV) is an organic combination of information equipment and military equipment. Utilizing swarm intelligence optimization algorithms [18], literature [19] has realized the problem of UAV trajectory planning in complex terrain environments. The existing multi-UAV collaborative mission planning model was revised, and a two-layer multitarget trajectory planning model was established to compensate for the adverse effects of imperfect constraint conditions of the mission planning model and simple mission requirements on practical applications; A global and local collaborative task planning method combining planning algorithms is proposed, which aims to solve the problems in practical applications such as a single application scenario and ideal environment in the process of UAV mission planning. This paper studies the problems of multi-UAV coordinated mission planning based on multi-task timing priority constraints, and proposes the joint execution of attack and damage assessment tasks.
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