Multi-unmanned aerial vehicle task allocation method based on improved global optimal brainstorm algorithm
A brainstorming and global optimal technology, applied in the field of unmanned aerial vehicle systems, can solve problems such as difficulty in obtaining combat effectiveness, increased time consumption, and increased communication traffic, to achieve collaborative and efficient allocation, accelerate the convergence process, and shorten running time Effect
Pending Publication Date: 2022-02-01
XI'AN PETROLEUM UNIVERSITY
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Problems solved by technology
However, this method needs to go through multiple negotiations, which will inevitably lead to increased communication traffic and time-consuming problems in large-scale task allocation. Secondly, the task allocation method based on the contract network is negotiated with a group of task subjects. When the numbers are inconsistent, it is difficult to achieve ideal combat effectiveness
[0005] Task planning methods based on genetic algorithm, ant colony algorithm, etc., have a large number of random search attempts in the optimization process, resulting in low efficiency and low precision when solving task allocation problems
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Embodiment 1
[0038] First, initialize the detection capability of the reconnaissance UAV to different targets [p ik ], the ability to attack UAVs against different targets [q jk ] and the value of the target. The instance data are randomly generated within the allowable range, and the generation method of the target threat degree (value) is as follows: v k =v l +(v u -v l ) × rand
[0039] where v l with v u are the upper and lower limits of the target value, respectively. The probability of RUAVs successfully capturing and tracking the target and the probability of UCAVs successfully destroying the target are both generated by the above method, and their ranges are shown in Table 1.
[0040] Table 1 data upper and lower limits
[0041]
[0042] 30 RUAVs, 40 UCAVs and 45 targets are set in this embodiment; N p Set to 10.
[0043] Next, initialize the distribution scheme population, each individual in the population can be divided into two parts, the distribution relationship ...
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The invention relates to the technical field of unmanned aerial vehicle systems, and concretely relates to a multi-unmanned aerial vehicle task allocation method based on an improved global optimal brainstorm algorithm. The method comprises the following steps: initializing the investigation capability of an investigation unmanned aerial vehicle for different targets, and the attack capability and target threat values of an attack unmanned aerial vehicle for different targets; designing a target task collaborative allocation model according to the attributes of the unmanned aerial vehicle and the attack demand of the target, and taking a value-cost function for maximally destroying the enemy target as a target function; initializing a task allocation scheme population, and taking an allocation relationship between the unmanned aerial vehicle and a target as an optimization variable; and carrying out iterative optimization by improving a global optimal brainstorm algorithm and taking the value-cost function as a target. Combat income maximization is taken as a target function, the investigation unmanned aerial vehicle, the target and the attack unmanned aerial vehicle are combined and considered uniformly, and a collaborative distribution model is adopted, so that rapid and efficient distribution of tasks of multiple unmanned aerial vehicles is realized.
Description
technical field [0001] The invention belongs to the technical field of unmanned aerial vehicle systems, and in particular relates to a multi-unmanned aerial vehicle mission planning method based on an improved global optimal brainstorming algorithm. Background technique [0002] Advances in science and technology have brought novel tools and methods, among which unmanned systems are gradually replacing manual operations. Due to its low cost, low risk, reliability and flexibility, UAVs are increasingly used in military and civilian fields. During the development of unmanned systems, mission planning of unmanned systems has become one of the most concerned issues. Among them, mission planning in complex three-dimensional hostile scenes is an important problem faced by UAVs. Multi-task planning is a mutual process. On the one hand, the design must consider the attributes of the UAV itself (single reconnaissance Reconnaissance unmanned aerial vehicle, RUAV, single attack unman...
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IPC IPC(8): G05D1/10
CPCG05D1/104
Inventor 高朝晖周谦高怡高广乐韩璐
Owner XI'AN PETROLEUM UNIVERSITY