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空中集群:近期应用与挑战

Aerial Swarms: Recent Applications and Challenges.

作者信息

Abdelkader Mohamed, Güler Samet, Jaleel Hassan, Shamma Jeff S

机构信息

Prince Sultan University, Riyadh, Saudi Arabia.

Systemtrio Electronics LLC, Abu Dhabi, UAE.

出版信息

Curr Robot Rep. 2021;2(3):309-320. doi: 10.1007/s43154-021-00063-4. Epub 2021 Jul 21.

DOI:10.1007/s43154-021-00063-4
PMID:34977595
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8294305/
Abstract

PURPOSE OF REVIEW

Currently, there is a large body of research on multi-agent systems addressing their different system theoretic aspects. Aerial swarms as one type of multi-agent robotic systems have recently gained huge interest due to their potential applications. However, aerial robot groups are complex multi-disciplinary systems and usually research works focus on specific system aspects for particular applications. The purpose of this review is to provide an overview of the main motivating applications that drive the majority of research works in this field, and summarize fundamental and common algorithmic components required for their development.

RECENT FINDINGS

Most system demonstrations of current aerial swarms are based on simulations, some have shown experiments using few 10 s of robots in controlled indoor environment, and limited number of works have reported outdoor experiments with small number of autonomous aerial vehicles. This indicates scalability issues of current swarm systems in real world environments. This is mainly due to the limited confidence on the individual robot's localization, swarm-level relative localization, and the rate of exchanged information between the robots that is required for planning safe coordinated motions.

SUMMARY

This paper summarizes the main motivating aerial swarm applications and the associated research works. In addition, the main research findings of the core elements of any aerial swarm system, state estimation and mission planning, are also presented. Finally, this paper presents a proposed abstraction of an aerial swarm system architecture that can help developers understand the main required modules of such systems.

摘要

综述目的

当前,针对多智能体系统的不同系统理论方面存在大量研究。空中集群作为多智能体机器人系统的一种类型,因其潜在应用最近引起了极大关注。然而,空中机器人集群是复杂的多学科系统,通常研究工作聚焦于特定应用的特定系统方面。本综述的目的是概述推动该领域大多数研究工作的主要激励性应用,并总结其发展所需的基本和通用算法组件。

最新发现

当前空中集群的大多数系统演示基于模拟,一些展示了在受控室内环境中使用少量(10个左右)机器人的实验,且仅有少数工作报道了使用少量自主飞行器的户外实验。这表明当前集群系统在现实世界环境中的可扩展性问题。这主要是由于对单个机器人定位、集群级相对定位以及规划安全协同运动所需的机器人之间信息交换速率缺乏信心。

总结

本文总结了主要的激励性空中集群应用及相关研究工作。此外,还介绍了任何空中集群系统核心要素——状态估计和任务规划的主要研究成果。最后,本文提出了一种空中集群系统架构的抽象,可帮助开发者理解此类系统的主要所需模块。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f196/8294305/8228bedd4390/43154_2021_63_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f196/8294305/1b14f8e678c7/43154_2021_63_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f196/8294305/3a37314eacd0/43154_2021_63_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f196/8294305/b5ee08d25301/43154_2021_63_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f196/8294305/8228bedd4390/43154_2021_63_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f196/8294305/1b14f8e678c7/43154_2021_63_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f196/8294305/3a37314eacd0/43154_2021_63_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f196/8294305/b5ee08d25301/43154_2021_63_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f196/8294305/8228bedd4390/43154_2021_63_Fig4_HTML.jpg

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