用逻辑模型统一多机器人系统的动态、计算与通信，实现任务可解性分析。
Knowledge in multi-robot systems: an interplay of dynamics, computation and communication
- 将混合动力系统转化为时序认知逻辑模型，建立知识推理框架。
- 推导出探索与聚集任务可解的充分知识条件，支持任务规划。
- 打通控制理论、分布式计算与认知逻辑的壁垒，适合跨领域研究者。
本文提出一个融合分布式多机器人系统与时序认知逻辑的框架。证明连续-离散混合系统与分布式计算中已有的知识逻辑模型相容，并通过推导探索与聚集任务可解的充分知识条件，展示其有效性。该框架分离了机器人的物理与计算层面，使控制理论与分布式计算方法得以独立应用。最后，提出一种从切换混合动力系统经抽象状态机表示，转化为时序-认知逻辑模型的系统化方法，促进控制理论、分布式计算与时序认知逻辑在多机器人系统中的交叉研究。
原文摘要 · Abstract (English)
In this paper, we provide a framework integrating distributed multi-robot systems and temporal epistemic logic. We show that continuous-discrete hybrid systems are compatible with logical models of knowledge already used in distributed computing, and demonstrate its usefulness by deriving sufficient epistemic conditions for exploration and gathering robot tasks to be solvable. We provide a separation of the physical and computational aspects of a robotic system, allowing us to decouple the problems related to each and directly use methods from control theory and distributed computing, fields that are traditionally distant in the literature. Finally, we demonstrate a novel approach for reasoning about the knowledge in multi-robot systems through a principled method of converting a switched hybrid dynamical system into a temporal-epistemic logic model, passing through an abstract state machine representation. This creates space for methods and results to be exchanged across the fields of control theory, distributed computing and temporal-epistemic logic, while reasoning about multi-robot systems.
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