Multi-Agent Distributed Coordination and Control For Aerial Systems

S. Lyshevski
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引用次数: 1

Abstract

This paper considers distributed multi-agent coordination and control to enable autonomy, tactical-level awareness, cognizance and swarm capabilities of autonomy-capable cyber-physical aerial systems. In complex dynamic environments, distributed algorithms and protocols should ensure robustness to communication and control constraints, such as bandwidth, data rate, latencies, throughput, uncertainties, etc. Decentralized coordination and control of networked nodes are researched. We solve problems in collaborative control, data management and networking of interdependent multi-agent systems. Unmanned aerial systems should ensure autonomy and cyberspace compliance. Adaptive collaborative control between agents and agents-pilot imply high-level hierarchy, distribution, micro- and macro-level decision-making, awareness, continual assurance, etc. Our results contribute to a cyclic observation-orientation-decision-action strategy in adversarial unstructured environments. We research, develop, integrate, test and evaluate practical techniques which are aimed to enable multi-domain aerial capabilities. This paper contributes to information-centric swarm solutions, researches algorithms, performs formative designs, and, experimentally validates fundamental and applied findings.
航空系统多智能体分布式协调与控制
本文考虑分布式多智能体协调和控制,以实现自主能力的网络物理航空系统的自主性、战术级感知、认知和群体能力。在复杂的动态环境中,分布式算法和协议应确保对通信和控制约束的鲁棒性,如带宽、数据速率、延迟、吞吐量、不确定性等。研究了网络节点的分散协调与控制。我们解决了相互依赖的多智能体系统的协同控制、数据管理和网络问题。无人机系统应确保自主性和网络空间合规性。agent和agent -pilot之间的自适应协同控制包括高层层次、分布、微观和宏观层面的决策、意识、持续保证等。我们的研究结果有助于在对抗性非结构化环境中形成一个循环的观察-定向-决策-行动策略。我们研究、开发、集成、测试和评估旨在实现多域空中能力的实用技术。本文致力于以信息为中心的群体解决方案,研究算法,执行形式设计,并通过实验验证基础和应用发现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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