Knowledge in multi-robot systems: an interplay of dynamics, computation and communication

2025-01-30

AI Summary

This study addresses the challenge of coordinated control in multi-robot systems, where dynamics, computation, and communication are deeply coupled. Methodologically, it proposes an interdisciplinary modeling framework integrating physical and cognitive layers, and— for the first time—systematically establishes a semantic mapping from switched hybrid dynamical systems to temporal-cognitive logic (TCL). By abstracting physical evolution as state machines and knowledge updates as distributed algorithms, the framework decouples these two processes, bridging control theory, distributed computing, and temporal-cognitive logic. Key contributions include: (i) deriving sufficient conditions for cognitive solvability of canonical tasks such as exploration and aggregation; and (ii) constructing the first knowledge-driven collaborative design framework supporting formal verification, thereby establishing a new paradigm for provably correct multi-robot system synthesis.

Technology Category

• Intelligent Robots: Multi-Robot Systems
• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Multiagent Systems: Coordination and Collaboration

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

We show that the hybrid systems perspective of distributed multi-robot systems is 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.

Problem

• Multi-Robot Systems
• Dynamics-Computation-Communication Integration
• Interdisciplinary Communication

Innovation

• hybrid systems perspective
• temporal-epistemic logic models
• multi-robot systems