航空计算与仿真技术专栏

智能无人机集群协同感知计算研究综述

  • 於志文 ,
  • 孙卓 ,
  • 程岳 ,
  • 郭斌
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  • 1.哈尔滨工程大学 计算机科学与技术学院,哈尔滨 150001
    2.西北工业大学 计算机学院,西安 710072
    3.中国航空工业集团公司 西安航空计算技术研究所,西安 710065
.E-mail: zhiwenyu@nwpu.edu.cn

收稿日期: 2024-07-05

  修回日期: 2024-07-14

  录用日期: 2024-07-24

  网络出版日期: 2024-08-20

基金资助

国家自然科学基金(61960206008)

A review of intelligent UAV swarm collaborative perception and computation

  • Zhiwen YU ,
  • Zhuo SUN ,
  • Yue CHENG ,
  • Bin GUO
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  • 1.College of Computer Science and Technology,Harbin Engineering University,Harbin 150001
    2.School of Computer Science,Northwestern Polytechnical University,Xi’an 710072
    3.Xi’an Aeronautics Computing Technique Research Institute,AVIC,Xi’an 710065

Received date: 2024-07-05

  Revised date: 2024-07-14

  Accepted date: 2024-07-24

  Online published: 2024-08-20

Supported by

National Natural Science Foundation of China(61960206008)

摘要

随着无人机智能化技术快速发展,无人机在智慧农业、灾后救援和战场侦察等领域具有广阔的应用前景。但是,感知计算能力有限的单无人机难以独立地完成实际应用中的复杂任务。因此,无人机集群协同感知计算技术被提出并成为未来无人机领域的主要研究方向。无人机集群协同感知计算技术是利用无线网络连接,多架无人机能够共享信息并协同地完成复杂的感知计算任务。从集群感知数据收集和协同感知策2方面,对无人机集群协同感知研究现状进行了深入调研分析。同时,详细归纳了无人机集群协同计算的最新研究进展,包括计算任务调度、算力资源分配以及数据存储策略。最后,探讨了智能无人机集群在协同感知计算方面的一些潜在研究问题和可行解决方法,如协同感知计算方法的可扩展性、多任务适应性以及开放无人机集群系统的协同感知计算方法等,为研究者对无人机集群协同感知计算的后续研究提供一定参考。

本文引用格式

於志文 , 孙卓 , 程岳 , 郭斌 . 智能无人机集群协同感知计算研究综述[J]. 航空学报, 2024 , 45(20) : 630912 -630912 . DOI: 10.7527/S1000-6893.2024.30912

Abstract

With the rapid development of intelligent UAV technology, UAVs have the vast prospects in many fields, such as smart agriculture, post-disaster rescue, and battlefield reconnaissance. However, the limited perceptual and computing capabilities of an individual UAV make it difficult to meet the complex environment and task requirements in practice. Therefore, the efficient collaborative perception and computation of UAV swarms have become the main development direction in the future UAV field. In this paper, we first present the basic concepts of collaborative perception and collaborative computation. For the collaborative perception, we review the latest progress in swarm perceptual data collection and collaborative perception strategy. For the collaborative computation, the optimal schemes of computation task scheduling, resource allocation and data catching are summarized and compared. In addition, we discuss the urgent problems of collaborative perception and computation from the perspective of UAVs. Some potential research directions are presented, providing a reference for the follow-up researchers.

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