A Method for Constructing Distributed Heterogeneous UAV Alliance Based on Resource Tree

Abstract

The invention discloses a resource tree-based distributed heterogeneous unmanned aerial vehicle alliance formation method, which is mainly used to generate efficient distributed heterogeneous unmanned aerial vehicles in real time when heterogeneous unmanned aerial vehicles carrying limited resources perform tasks in unknown areas. machine alliance. This method is based on the premise that a single UAV (for fixed-wing UAVs) is difficult to effectively complete complex tasks, and mainly considers how to build an efficient heterogeneous UAV alliance to perform complex tasks. In the present invention, firstly, UAVs are used to search for task targets in a designated area, and after finding a certain task, it is judged whether it is necessary to send alliance request information, and the UAV receiving the alliance request information judges whether to respond, thereby obtaining candidate alliances, and then using The distributed alliance construction method based on resource tree obtains the most efficient UAV alliance. The method proposed by the invention can be used to construct an efficient distributed heterogeneous UAV alliance in real time when using heterogeneous UAVs to perform complex tasks in an unknown environment.

Description

technical field [0001] The invention relates to a method for constituting a distributed heterogeneous unmanned aerial vehicle alliance based on a resource tree, and belongs to the technical field of task assignment of unmanned aerial vehicles when executing tasks. Background technique [0002] In recent years, Unmanned Aerial Vehicles (UAVs) have been widely used in various fields to perform various tasks. Mission planning for multi-UAVs is usually divided into two parts: task assignment and path planning. We can interpret the task allocation problem as a combinatorial optimization problem (NP-hard combinatorial optimization problem) whose correctness can be verified in polynomial time. The complexity of task assignment increases with the number of drones and tasks. Heuristic algorithms, such as ant colony optimization (ACO), genetic algorithm (GA), particle swarm optimization (PSO) and simulated annealing (SA), etc. have been used to provide reasonable solutions to task a...

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Problems solved by technology

Moreover, there is a situation that the UAV base station cannot obtain prior conditions such as the location of the mission target and the required resources in advance, which also increases the difficulty of how to allocate tasks reasonably

In summary, since the location of the mission target and the required resources are unknown, and the amount of resources carried by a single UAV is limited, a single UAV cannot complete complex tasks alone, so how to efficiently form a UAV alliance has become a major issue. technical problem

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