• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

为多无人机网络设计一个分布式协同模拟器。

Devising a Distributed Co-Simulator for a Multi-UAV Network.

作者信息

Park Seongjoon, La Woong Gyu, Lee Woonghee, Kim Hwangnam

机构信息

School of Electrical Engineering, Korea University, Seoul 02841, Korea.

出版信息

Sensors (Basel). 2020 Oct 30;20(21):6196. doi: 10.3390/s20216196.

DOI:10.3390/s20216196
PMID:33143208
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7663101/
Abstract

Practical evaluation of the Unmanned Aerial Vehicle (UAV) network requires a lot of money to build experiment environments, which includes UAVs, network devices, flight controllers, and so on. To investigate the time-sensitivity of the multi-UAV network, the influence of the UAVs' mobility should be precisely evaluated in the long term. Although there are some simulators for UAVs' physical flight, there is no explicit scheme for simulating both the network environment and the flight environments simultaneously. In this paper, we propose a novel co-simulation scheme for the multiple UAVs network, which performs the flight simulation and the network simulation simultaneously. By considering the dependency between the flight status and networking situations of UAV, our work focuses on the consistency of simulation state through synchronization among simulation components. Furthermore, we extend our simulator to perform multiple scenarios by exploiting distributed manner. We verify our system with respect to the robustness of time management and propose some use cases which can be solely simulated by this.

摘要

对无人机(UAV)网络进行实际评估需要大量资金来构建实验环境,其中包括无人机、网络设备、飞行控制器等。为了研究多无人机网络的时间敏感性,需要长期精确评估无人机移动性的影响。虽然有一些用于无人机物理飞行的模拟器,但没有同时模拟网络环境和飞行环境的明确方案。在本文中,我们提出了一种针对多无人机网络的新型联合仿真方案,该方案可同时进行飞行仿真和网络仿真。通过考虑无人机飞行状态与网络情况之间的依赖性,我们的工作通过仿真组件之间的同步来关注仿真状态的一致性。此外,我们通过利用分布式方式扩展模拟器以执行多个场景。我们针对时间管理的鲁棒性验证了我们的系统,并提出了一些仅可由此进行模拟的用例。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bde2/7663101/2a6380a9c2b4/sensors-20-06196-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bde2/7663101/06cc9193f4b3/sensors-20-06196-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bde2/7663101/3ab7863cda40/sensors-20-06196-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bde2/7663101/f1bcd48d8f80/sensors-20-06196-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bde2/7663101/b68c9e7eb874/sensors-20-06196-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bde2/7663101/9e36633e8e41/sensors-20-06196-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bde2/7663101/821e1820401f/sensors-20-06196-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bde2/7663101/943d3e97bb82/sensors-20-06196-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bde2/7663101/58f5d81cc6c0/sensors-20-06196-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bde2/7663101/0f63871e6c6c/sensors-20-06196-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bde2/7663101/2a6380a9c2b4/sensors-20-06196-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bde2/7663101/06cc9193f4b3/sensors-20-06196-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bde2/7663101/3ab7863cda40/sensors-20-06196-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bde2/7663101/f1bcd48d8f80/sensors-20-06196-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bde2/7663101/b68c9e7eb874/sensors-20-06196-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bde2/7663101/9e36633e8e41/sensors-20-06196-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bde2/7663101/821e1820401f/sensors-20-06196-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bde2/7663101/943d3e97bb82/sensors-20-06196-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bde2/7663101/58f5d81cc6c0/sensors-20-06196-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bde2/7663101/0f63871e6c6c/sensors-20-06196-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bde2/7663101/2a6380a9c2b4/sensors-20-06196-g010.jpg

相似文献

1
Devising a Distributed Co-Simulator for a Multi-UAV Network.为多无人机网络设计一个分布式协同模拟器。
Sensors (Basel). 2020 Oct 30;20(21):6196. doi: 10.3390/s20216196.
2
Formation Flight of Multiple UAVs via Onboard Sensor Information Sharing.基于机载传感器信息共享的多无人机编队飞行
Sensors (Basel). 2015 Jul 17;15(7):17397-419. doi: 10.3390/s150717397.
3
Joint UAVs' Load Balancing and UEs' Data Rate Fairness Optimization by Diffusion UAV Deployment Algorithm in Multi-UAV Networks.多无人机网络中基于扩散无人机部署算法的联合无人机负载均衡与用户设备数据速率公平性优化
Entropy (Basel). 2021 Nov 7;23(11):1470. doi: 10.3390/e23111470.
4
UAV Flight and Landing Guidance System for Emergency Situations .UAV 应急飞行与着陆引导系统。
Sensors (Basel). 2019 Oct 15;19(20):4468. doi: 10.3390/s19204468.
5
Distributed adaptive fault-tolerant close formation flight control of multiple trailing fixed-wing UAVs.多架后缘固定翼无人机的分布式自适应容错紧密编队飞行控制
ISA Trans. 2020 Nov;106:181-199. doi: 10.1016/j.isatra.2020.07.005. Epub 2020 Jul 9.
6
Development of Cloud-Based UAV Monitoring and Management System.基于云的无人机监测与管理系统的开发
Sensors (Basel). 2016 Nov 15;16(11):1913. doi: 10.3390/s16111913.
7
Genetic Algorithm-Based Cooperative Coding and Caching Data Dissemination Scheme in Multi-UAV-Enabled Internet of Vehicles.基于遗传算法的多无人机车载互联网协作编码与缓存数据分发方案
Sensors (Basel). 2024 Jul 9;24(14):4443. doi: 10.3390/s24144443.
8
Trajectory Design for Multi-UAV-Aided Wireless Power Transfer toward Future Wireless Systems.面向未来无线系统的多无人机辅助无线电能传输轨迹设计
Sensors (Basel). 2022 Sep 10;22(18):6859. doi: 10.3390/s22186859.
9
Reinforcement Learning Based Topology Control for UAV Networks.基于强化学习的无人机网络拓扑控制。
Sensors (Basel). 2023 Jan 13;23(2):921. doi: 10.3390/s23020921.
10
An Optimal Routing Algorithm for Unmanned Aerial Vehicles.一种用于无人机的最优路径算法。
Sensors (Basel). 2021 Feb 9;21(4):1219. doi: 10.3390/s21041219.

引用本文的文献

1
Energy-Efficient Deployment Simulator of UAV-Mounted Base Stations Under Dynamic Weather Conditions.动态天气条件下无人机挂载基站的节能部署模拟器
Sensors (Basel). 2025 Jun 11;25(12):3648. doi: 10.3390/s25123648.
2
Guest Editorial Special Issue on Time-Sensitive Networks for Unmanned Aircraft Systems.客座编辑特刊:关于无人机系统的时间敏感网络。
Sensors (Basel). 2021 Sep 13;21(18):6132. doi: 10.3390/s21186132.
3
An MPTCP-Based Transmission Scheme for Improving the Control Stability of Unmanned Aerial Vehicles.一种基于多路径传输控制协议(MPTCP)的用于提高无人机控制稳定性的传输方案。

本文引用的文献

1
Leader-Following Consensus and Formation Control of VTOL-UAVs with Event-Triggered Communications .基于事件触发通信的 VTOL-UAV 的领导者跟随一致性和编队控制。
Sensors (Basel). 2019 Dec 12;19(24):5498. doi: 10.3390/s19245498.
2
Devising Mobile Sensing and Actuation Infrastructure with Drones.利用无人机设计移动传感与驱动基础设施。
Sensors (Basel). 2018 Feb 19;18(2):624. doi: 10.3390/s18020624.
Sensors (Basel). 2021 Apr 15;21(8):2791. doi: 10.3390/s21082791.