Multi-agent system for formation flying missions

S. Mandutianu, F. Hadaegh, P. Elliot
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引用次数: 17

Abstract

Concerns use of spacecraft as autonomous coordinated teams. Generalized reasoning capability offered by advanced distributed software technology and AI can cope with unexpected events and uncertainty, and so close the loop of perception, decision and eventually deliberation. The team members play interchangeable roles and negotiate about the task. We present a multi-agent system to provide a high degree of autonomy and support for coordination among team members. We use JPL formation flying mission initial architectures as benchmark. Our target is to avoid inconsistencies/disagreements between two or more participants in a collaborative context, increase the system's fault tolerance in cases such as loss of a member while the system still operates reliably. We address cooperation between collaborating independent autonomous agents. In a top-down organization agents are coordinated hierarchically, where the agents at the top of the hierarchy make the majority of the intelligent group decisions. In a more structured but still hierarchical organization, lower-level agents exercise more intelligence. A lower-level agent can advance a plan for the others to follow, and a higher-rank agent decides on the best plans. Although more rigid, the centralized intelligence organization allows for less communication among agents, so is more straightforward to implement. The decentralized approach requires more communication, but the intelligence is truly distributed, which makes for a more flexible, adaptive and efficient organization.
编队飞行任务多智能体系统
关注航天器作为自主协调团队的使用。先进的分布式软件技术和人工智能提供的广义推理能力可以应对意外事件和不确定性,从而完成感知、决策和最终审议的循环。团队成员扮演可互换的角色,并就任务进行协商。我们提出了一个多智能体系统,为团队成员之间的协调提供高度的自主性和支持。我们使用JPL编队飞行任务初始架构作为基准。我们的目标是避免协作环境中两个或更多参与者之间的不一致/分歧,在系统仍然可靠运行的情况下增加系统的容错性,例如成员丢失。我们处理协作的独立自主代理之间的合作。在自顶向下的组织中,代理是分层协调的,其中位于层次结构顶部的代理做出大多数智能群体决策。在一个更结构化但仍然是分层的组织中,较低级别的代理会行使更多的智能。级别较低的代理可以提出一个计划,让其他代理遵循,而级别较高的代理决定最佳计划。尽管集中式情报组织更严格,但它允许代理之间的通信更少,因此实现起来更直接。去中心化的方法需要更多的沟通,但智能是真正的分布式,这使得组织更灵活,适应性更强,效率更高。
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