一种用于大规模集群仿真的无人平台状态更新方法
By dividing the unmanned platform cluster into rotorcraft and fixed-wing clusters and adopting GPU parallel computing and publish/subscribe architecture, the problems of large computational load and slow speed of unmanned platform cluster simulation system are solved, and efficient updates of large-scale cluster status are achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- COMP APPL TECH INST OF CHINA NORTH IND GRP
- Filing Date
- 2025-07-14
- Publication Date
- 2026-07-17
AI Technical Summary
Existing unmanned platform cluster simulation systems are computationally intensive and slow during state updates, and cannot support large-scale, accurate dynamic equation calculations with thousands of nodes or more.
The unmanned platform cluster is divided into rotorcraft clusters and fixed-wing clusters. Status updates are performed based on cluster type and control commands. Data distribution is carried out using GPU parallel computing and a publish/subscribe architecture, which simplifies network communication and reduces hardware resource consumption.
It supports state calculation of ultra-large-scale unmanned system clusters with more than a thousand nodes, consumes few hardware resources, and can achieve state calculation of clusters with a scale of thousands with a consumer-grade image processor.
Smart Images
Figure CN120802668B_ABST