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Bottom-up motion and task coordination for loosely-coupled multi-agent systems with dependent local tasks

机译:具有相关本地任务的松耦合多主体系统的自下而上运动和任务协调

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We propose a bottom-up motion and task coordination scheme for loosely-coupled multi-agent systems under dependent local tasks. Instead of defining a global task for the whole team, each agent is assigned locally a task as syntactically co-safe linear temporal logic formulas that specify both motion and action requirements. Inter-agent dependency is introduced by collaborative actions of which the execution requires multiple agents' collaboration. The proposed solution contains an offline initial plan synthesis, an on-line request-reply messages exchange and a real-time plan adaptation algorithm. It is distributed in that any decision is made locally based on local computation and local communication within neighboring agents. It is scalable and resilient to agent failures as the dependency is formed and removed dynamically based on the plan execution status and agent capabilities, instead of pre-assigned agent identities. The overall scheme is demonstrated by a simulated scenario.
机译:我们提出了一个自下而上的运动和任务协调方案,用于在依赖于本地任务下松散耦合的多智能体系。而不是为整个团队定义全局任务,每个代理将本地分配一个任务,作为语法共同安全的线性时间逻辑公式,用于指定运动和操作要求。代理间依赖项是通过执行需要多个代理的协作的协同行为引入。所提出的解决方案包含离线初始计划合成,一个在线请求 - 回复消息交换和实时计划适应算法。它被分发,因为在邻近代理中的本地计算和本地通信基础上进行任何判定。它是可伸缩的,并且对代理故障的弹性失败,因为基于计划执行状态和代理能力,而不是预先分配的代理商标识动态地形成和删除依赖性。通过模拟场景证明了整体方案。

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