Multi-unmanned-aerial-vehicle intelligent cooperation observe/act method for multiple dynamic targets

Abstract

The invention discloses a multi-unmanned-aerial-vehicle intelligent cooperation observe / act method for multiple dynamic targets. The method includes the steps: firstly, discretizing a task area, and making the motions of unmanned aerial vehicles correspond to the motions of grids in a discrete space on the basis of the mobility of the unmanned aerial vehicles; secondly, on the basis of an ant colony algorithm, performing cooperation searching in the task area, wherein each ant agent represents one unmanned aerial vehicle, has positioning, sensing, memorizing, moving, attacking, communicating and self-updating capabilities like an unmanned aerial vehicle platform, and also is restricted by the performance of the unmanned aerial vehicles; and thirdly, the ant agents enabling, for searched targets, the unmanned aerial vehicles to track and attack moving targets through a guidance method based on a parallel approaching method. During the process, ant searching and ant tracking and attacking are carried out alternatively, thereby achieving continuous observe / act effects for the task area.

Description

technical field [0001] The invention relates to a multi-UAV intelligent cooperative inspection method for multi-dynamic targets, which belongs to the field of mission planning. Background technique [0002] Unmanned Aerial Vehicle (UAV) system is a kind of unmanned aerial robot system that can be autonomously controlled or remotely controlled. With the continuous development and application of various new technologies such as automation and computers, the technology of UAVs is more intensive, the structure is becoming more and more complex, and the functions are also more powerful. UAVs are expected to gradually enter the main combat weapons of the Air Force around 2020. The ranks will partially replace manned fighters and bombers, and undertake most of the air defense suppression and some air strike tasks. According to the OODA (Observe-Orient-Decide-Act) model, the U.S. Air Force Research Laboratory divides the autonomous control capabilities of UAVs into 10 levels: remot...

AI Technical Summary

Problems solved by technology

However, due to the limitations of existing technical conditions, the overall research is basically in its infancy. Compared with foreign research, my country has a certain gap in the conceptual research, system design, theoretical methods, and practical applications of multi-UAV autonomous cooperative control. Therefore, further in-depth research in this area is urgently needed

However, most of the foreign studies on multi-UAV mission planning based on self-organization, such as self-organization of cooperative reconnaissance missions and self-organization of cooperative search tasks, are mostly aimed at static targets, without considering the movement of targets, which do not conform to the actual situation.

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