无人智能集群

张军; 福田敏男; 林德福; Florian Holzapfel

doi:10.1016/j.eng.2022.04.001

工程（英文） ›› 2022, Vol. 12 ›› Issue (5) : 1 -2. DOI: 10.1016/j.eng.2022.04.001

无人智能集群

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Editorial for the Special Issue on Unmanned Intelligent Cluster

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网络协作自动系统的最新研究进展为其广泛应用中提高系统的质量提供了可能。在过去的几十年中，嵌入式处理器、传感器、通信和网络技术的进步提升了人们对网络协作自动系统、多机器人系统和分布式传感器网络在制造、物流、过程监控、增强态势感知、工厂安全、检查、安保和救援行动中的兴趣。这些进步使个体自动化系统更加实用，也使得对协作系统（其能力由团队而不是由特别有能力的个体来表达）开发的研究成为可能。协作系统尤其适用于需要数量和难度各不相同的复杂任务，如货物运输、分布式装配、车辆协调策略和基础设施检查。此外，与不是特别有能力的个体系统相比，协作系统的主要优势之一在于其因冗余而提高了可靠性。

本期无人智群专题包含有关无人蜂群系统相关理论和实践方面的最新发展和研究成果的原创性贡献和观点。在这个问题上，张福彪等通过结合认知特征，在无人智能集群（UniC）设计中提出以人为本的愿景。在这个愿景下，分布式无人系统和人类通过知识联系起来，实现认知。这些学者的工作介绍了UniC的整体概念，以及它的智能来源、分层架构和社会接受度。此外，还总结了当前最先进的使能技术、未来趋势和在实现这一愿景方面仍然存在的开放性问题，以解决该领域仍然存在的挑战。

同样在这个问题上，孟非等开发了一种用于腿足机器人的爆炸电动执行器和相关控制方法。他们的工作引入了一种高功率密度的无级变速器，可以连续调节输出速度与扭矩的比率。通过利用基于相变材料的散热结构和积分扭矩控制方法，他们开发的执行器被证明可以在动态运动期间的特定时刻提供高峰值速度或高峰值扭矩。

最后，陈杰等评论称，自主智能无人系统（AIS）是一个新兴的跨学科领域，它依靠大数据和人工智能（AI）来创建具有集成任务和运动规划以及决策和推理能力的无人系统。与可能基于规则或由人类或其他机器远程控制的常见无人平台相比，AIS具有几个独特的性质：提高自主性、智能和协作性水平。因此，AIS是AI研究的最终目标，并且AIS研究为人工通用智能（AGI）提供了一条有前景的道路。

正如陈杰等在文章中指出的那样，对自主无人系统的研究是一项永无止境的工作。鉴于强大的人工智能技术和数据处理深度学习的发展，智能自主无人系统因其具有广泛的应用和提供附加值的能力，将成为未来几年的主要技术和经济动力之一。特别是，入侵无人系统的检测和捕捉，以及使用仿生和基于事件的神经视觉传感器的先进传感和感知技术，是近期需要研究的关键问题。

我们希望本期无人智群专题的文章有助于培养创新思维，拓宽我们在无人智能系统开发方面的视野。我们感谢所有作者的投稿和杰出贡献，以及许多帮助审稿并为编辑和作者提供改进建议的个人。我们要特别感谢主编周济和Engineering期刊的编委会，感谢他们为我们提供了组织本期无人智群专题的机会。最后重要的是，我们感谢编辑韩志锐和王雪，她们为确保本期专题的及时处理和出版提供了宝贵的帮助。