Abstract
Unmanned aerial vehicles (UAVs) received an unprecedented surge of people’s interest worldwide in recent years. This paper investigates the specific problem of cooperative mission planning for multiple UAVs on the battlefield from a hierarchical decision-making perspective. From the view of the actual mission planning issue, the two key problems to be solved in UAV collaborative mission planning are mission allocation and route planning. In this paper, both of these problems are taken into account via a hierarchical decision-making model. Firstly, we use a target clustering algorithm to divide the original targets into target subgroups, where each target subgroup contains multiple targets. Secondly, a fuzzy ant colony algorithm is used to calculate the global path between target subgroups for a single-target group. Thirdly, a fuzzy ant colony algorithm is also used to calculate the local path between multiple targets for a single-target subgroup. After three levels of decision-making, the complete path for multiple UAVs can be obtained. In order to improve the efficiency of a collaborative task between different types of UAVs, a cooperative communication strategy is developed, which can reduce the number of UAVs performing tasks. Finally, experimental results demonstrate the effectiveness of the proposed cooperative mission planning and cooperative communication strategy for multiple UAVs.
Highlights
We investigated the specific problem of cooperative mission planning for multiple
The specific problem was modeled as a mathematical model for hierarchical decision-making, considering the existing resources and constraints
In order to plan the flight path for Unmanned aerial vehicles (UAVs), we proposed a fuzzy ant colony algorithm to design the rule of updating quantities of an ant on the path
Summary
The unmanned aerial vehicle is a new type of combat platform with independent flight capability and independent execution capability, which received huge interest and unprecedented attention worldwide [1]. The UAVs receive increasingly large amounts of attention in accomplishing cooperative tasks since their flights can be controlled via a workstation on the ground. A huge amount of research focused on the communication of UAV networks for the cooperative mission planning of UAVs [6]. Only a few studies demonstrated how to deploy UAVs in specific battlefields for cooperative mission planning. Due to the limitation of current hardware and technical conditions, how to reasonably dispatch UAVs to perform cooperative tasks and choose the best reconnaissance route for a group or cluster of UAVs is of great significance to operations [7,8].
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