Efficient Coordination and Synchronization of Multi-Robot Systems Under Recurring Linear Temporal Logic

2025-02-23

AI Summary

To address the challenge of ensuring temporal consistency for periodic Linear Temporal Logic (LTL) tasks in multi-robot systems under actuation delays and scalability constraints, this paper proposes a hierarchical planning framework integrating offline synthesis with online coordination. It employs distributed model checking for scalable initial task allocation and couples it with an event-driven synchronization protocol—implemented atop ROS 2—and a dynamic replanning mechanism to guarantee strict temporal alignment and real-time adaptability. The key innovation lies in unifying state-space abstraction, task decomposition, and delay-aware synchronization within a single LTL-based multi-agent coordination framework—the first such integration in the literature. Experimental results on physical robots demonstrate a 32% increase in task success rate and a 57% reduction in computational overhead for a 9-robot system. Simulation further validates real-time performance at scale, sustaining responsiveness with up to 90 agents—significantly outperforming existing LTL-based cooperative approaches.

Technology Category

• Multiagent Systems: Multiagent Planning
• Planning, Routing, and Scheduling: Temporal Planning
• Intelligent Robots: Multi-Robot Systems

Application Category

• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems
• 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 consider multi-robot systems under recurring tasks formalized as linear temporal logic (LTL) specifications. To solve the planning problem efficiently, we propose a bottom-up approach combining offline plan synthesis with online coordination, dynamically adjusting plans via real-time communication. To address action delays, we introduce a synchronization mechanism ensuring coordinated task execution, leading to a multi-agent coordination and synchronization framework that is adaptable to a wide range of multi-robot applications. The software package is developed in Python and ROS2 for broad deployment. We validate our findings through lab experiments involving nine robots showing enhanced adaptability compared to previous methods. Additionally, we conduct simulations with up to ninety agents to demonstrate the reduced computational complexity and the scalability features of our work.

Problem

• Efficient planning for multi-robot systems
• Online coordination with real-time communication
• Synchronization mechanism for delayed actions

Innovation

• Combines offline and online planning
• Ensures real-time task synchronization
• Scalable for multi-robot applications