CN-121613947-B - Unmanned aerial vehicle cluster task management method and device, computer equipment and storage medium

CN121613947BCN 121613947 BCN121613947 BCN 121613947BCN-121613947-B

Abstract

The invention discloses an unmanned aerial vehicle cluster task management method, a device, computer equipment and a storage medium, wherein the method comprises the steps of obtaining a target task to be executed of an unmanned aerial vehicle cluster; the target task comprises a plurality of continuous animation processes, wherein each animation process comprises navigation point information of a plurality of unmanned aerial vehicles, a first frame of plane coordinate set and a last frame of plane coordinate set in each animation process are obtained according to the navigation point information, a navigation point mapping table between two adjacent animation processes is calculated through an optimal matching algorithm based on the first frame of plane coordinate set and the last frame of plane coordinate set, an accumulated mapping relation is generated based on the navigation point mapping table, unmanned aerial vehicle navigation points in each animation process are subjected to integral exchange optimization to obtain optimized navigation points of each animation process, path planning is carried out on the optimized navigation points to obtain a navigation point planning result of the target task, and unmanned aerial vehicle clusters are controlled to execute the target task according to the navigation point planning result. The invention can improve the task execution efficiency and precision of the unmanned aerial vehicle cluster.

Inventors

Xu Chenzhuo
ZHANG XUYU
HUANG XIN

Assignees

深圳大漠大智控技术有限公司

Dates

Publication Date: 20260512
Application Date: 20260129

Claims (9)

1. The unmanned aerial vehicle cluster task management method is characterized by comprising the following steps of: The method comprises the steps of obtaining a target task to be executed by an unmanned aerial vehicle cluster, wherein the target task comprises a plurality of continuous animation processes, and each animation process comprises waypoint information of a plurality of unmanned aerial vehicles; Acquiring a first frame aircraft coordinate set and a tail frame aircraft coordinate set in each animation process according to the waypoint information; Calculating a waypoint mapping table between two adjacent animation processes through an optimal matching algorithm based on the first frame aircraft coordinate set and the tail frame aircraft coordinate set; generating an accumulated mapping relation based on the waypoint mapping table, and carrying out overall exchange optimization on unmanned aerial vehicle waypoints in each animation process to obtain optimized waypoints in each animation process; performing path planning on the optimized waypoints to obtain a waypoint planning result of the target task, and controlling the unmanned aerial vehicle cluster to execute the target task according to the waypoint planning result; Generating an accumulated mapping relation based on the waypoint mapping table, and performing overall exchange optimization on unmanned aerial vehicle waypoints in each animation process to obtain optimized waypoints in each animation process, wherein the method comprises the following steps: based on the waypoint mapping table, taking the first animation process as a reference, acquiring waypoint information of the unmanned aerial vehicle in the former animation process in the latter animation process in the two adjacent animation processes, and generating an accumulated mapping relation from the first animation process to each subsequent animation process; And carrying out integral exchange on the unmanned aerial vehicle waypoints in each animation process according to the accumulated mapping relation to obtain an animation process containing the optimized waypoints.
2. The unmanned aerial vehicle cluster task management method according to claim 1, wherein the acquiring the target task to be executed by the unmanned aerial vehicle cluster comprises: Recording each animation process in the target task as a i and each unmanned aerial vehicle in the animation process a i as a ij , wherein i=1, 2..k, j=1, 2..w, k represents the total number of animation processes and w represents the total number of frames of the unmanned aerial vehicle in each animation process a i ; judging whether an animation process of which the unmanned aerial vehicle frame time is not w exists or not; If the animation process of which the unmanned aerial vehicle frame times are not w is judged to exist, the corresponding animation process is marked to be illegal and removed.
3. The unmanned aerial vehicle cluster task management method of claim 2, wherein the acquiring the first frame aircraft coordinate set and the last frame aircraft coordinate set in each animation process according to the waypoint information comprises: Acquiring a first frame coordinate A ijS of each unmanned aerial vehicle A ij in each animation process, and constructing a first frame aircraft coordinate set A iS according to a first frame coordinate A ijS of each unmanned aerial vehicle A ij ; And acquiring the tail frame coordinate A ijE of each unmanned aerial vehicle A ij in each animation process, and constructing a tail frame aircraft coordinate set A iE according to the tail frame coordinate A ijE of each unmanned aerial vehicle A ij .
4. The unmanned aerial vehicle cluster task management method of claim 2, wherein the calculating the waypoint mapping table between two adjacent animation processes by an optimal matching algorithm based on the first frame aircraft coordinate set and the last frame aircraft coordinate set comprises: Inputting a tail frame coordinate set of a previous animation process and a first frame coordinate set of a next animation process in two adjacent animation processes into a KM algorithm, and outputting a navigation point mapping table T (i,i+1) which enables the total moving distance of all unmanned aerial vehicles to be shortest by the KM algorithm, wherein i=1, 2.
5. The unmanned aerial vehicle cluster task management method of claim 1, wherein the acquiring, based on the waypoint mapping table and based on the first animation process, waypoint information of the unmanned aerial vehicle in the previous animation process in the next animation process, thereby generating an accumulated mapping relationship from the first animation process to each subsequent animation process, comprises: When other animation processes except the first animation process are updated, performing waypoint mapping based on the updated animation processes, and generating a new accumulated mapping relation.
6. The unmanned aerial vehicle cluster task management method according to claim 1, wherein the performing path planning on the optimized waypoints to obtain a waypoint planning result of the target task, and controlling the unmanned aerial vehicle cluster to execute the target task according to the waypoint planning result, comprises: And planning every two adjacent two animation processes according to the execution sequence of the animation processes in the target task to obtain the navigation point planning result.
7. An unmanned aerial vehicle cluster task management device, comprising: the system comprises a task acquisition unit, a target task processing unit and a target processing unit, wherein the task acquisition unit is used for acquiring a target task to be executed by an unmanned aerial vehicle cluster, the target task comprises a plurality of continuous animation processes, and each animation process comprises waypoint information of a plurality of unmanned aerial vehicles; The set acquisition unit is used for acquiring a first frame aircraft coordinate set and a tail frame aircraft coordinate set in each animation process according to the waypoint information; The mapping calculation unit is used for calculating a waypoint mapping table between two adjacent animation processes through an optimal matching algorithm based on the first frame aircraft coordinate set and the tail frame aircraft coordinate set; the navigation point optimizing unit is used for generating an accumulated mapping relation based on the navigation point mapping table, and carrying out overall exchange optimization on unmanned aerial vehicle navigation points in each animation process to obtain optimized navigation points in each animation process; The planning control unit is used for carrying out path planning on the optimized waypoints to obtain a waypoint planning result of the target task, and controlling the unmanned aerial vehicle cluster to execute the target task according to the waypoint planning result; The waypoint optimizing unit includes: The mapping generation unit is used for acquiring the waypoint information of the unmanned aerial vehicle in the former animation process in the latter animation process in the two adjacent animation processes based on the first animation process, thereby generating an accumulated mapping relation from the first animation process to each subsequent animation process; And the waypoint exchange unit is used for carrying out integral exchange on the unmanned aerial vehicle waypoints in each animation process according to the accumulated mapping relation to obtain an animation process containing the optimized waypoints.
8. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the unmanned aerial vehicle cluster task management method of any of claims 1 to 6 when the computer program is executed.
9. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the unmanned aerial vehicle cluster task management method according to any of claims 1 to 6.

Description

Unmanned aerial vehicle cluster task management method and device, computer equipment and storage medium Technical Field The invention relates to the technical field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle cluster task management method, an unmanned aerial vehicle cluster task management device, computer equipment and a storage medium. Background With the development of unmanned aerial vehicle cluster technology, unmanned aerial vehicle clusters are applied in multiple fields in a large scale by virtue of the advantages of distributed coordination, wide coverage, strong fault tolerance and the like. In the actual complex task, the formation needs to continuously execute multi-stage tasks, and the connection fluency of each stage directly determines the overall efficiency and accuracy. From a technical perspective, a complete unmanned cluster task can be considered a concatenation of multiple discrete animation segments. The animation is the representation of the core information such as the motion state, the gesture track, the position change, the collaborative logic and the like of each task stage of the cluster, and carries the behavior data and the control instruction of the corresponding stage. Different stages of animation have natural discontinuities in parameters, time sequence and the like due to task characteristics. In task execution, efficient matching and linking of animation information is key to improving efficiency. The problems of disturbance of the posture, deviation of the position and the like are not easy to cause when the matching is not accurate, and even cluster collision and task interruption are caused. Therefore, the matching algorithm is used for quickly aligning the core information of each animation, so that seamless splicing is realized, and the method is a necessary way for improving the task efficiency and stability of the cluster. However, the current field still faces a plurality of challenges, namely complex dimension, isomerism and huge volume of animation data, so that the calculation complexity of an algorithm is improved, and the information distortion is easy to cause due to external disturbance, so that the requirement on the robustness of the algorithm is higher. The existing method is multiple in adaptation to a single scene, is difficult to consider speed, precision and anti-interference capability, and cannot meet the requirements of complex tasks. Disclosure of Invention The embodiment of the invention provides a method, a device, computer equipment and a storage medium for managing unmanned aerial vehicle cluster tasks, aiming at improving the task execution efficiency of unmanned aerial vehicle clusters. In a first aspect, an embodiment of the present invention provides a method for managing a task of an unmanned aerial vehicle cluster, including: The method comprises the steps of obtaining a target task to be executed by an unmanned aerial vehicle cluster, wherein the target task comprises a plurality of continuous animation processes, and each animation process comprises waypoint information of a plurality of unmanned aerial vehicles; Acquiring a first frame aircraft coordinate set and a tail frame aircraft coordinate set in each animation process according to the waypoint information; Calculating a waypoint mapping table between two adjacent animation processes through an optimal matching algorithm based on the first frame aircraft coordinate set and the tail frame aircraft coordinate set; generating an accumulated mapping relation based on the waypoint mapping table, and carrying out overall exchange optimization on unmanned aerial vehicle waypoints in each animation process to obtain optimized waypoints in each animation process; And carrying out path planning on the optimized waypoints to obtain a waypoint planning result of the target task, and controlling the unmanned aerial vehicle cluster to execute the target task according to the waypoint planning result. In a second aspect, an embodiment of the present invention provides an unmanned aerial vehicle cluster task management device, including: the system comprises a task acquisition unit, a target task processing unit and a target processing unit, wherein the task acquisition unit is used for acquiring a target task to be executed by an unmanned aerial vehicle cluster, the target task comprises a plurality of continuous animation processes, and each animation process comprises waypoint information of a plurality of unmanned aerial vehicles; The set acquisition unit is used for acquiring a first frame aircraft coordinate set and a tail frame aircraft coordinate set in each animation process according to the waypoint information; The mapping calculation unit is used for calculating a waypoint mapping table between two adjacent animation processes through an optimal matching algorithm based on the first frame aircraft coordinate set and the tail frame aircraft coordinate