MAOP: Multi-Agent Orchestration Platform for Robotic Applications

摘要

As more heterogenous robotic systems are deployed in industrial settings, challenges in coordination, integration, and task management have grown. This paper presents MAOP, a Multi-Agent Orchestration Platform designed to unify the control and collaboration of diverse agents—including robots, infrastructure, and humans—within a single, scalable framework. MAOP leverages principles from multi-agent orchestration and multi-robot systems to enable intelligent task decomposition, dynamic agent allocation, and real-time system adaptation. The platform is composed of five modular components: Agent Manager, Task Manager, Interface Handler, Interaction Manager, and Watchdog, each contributing to robust, fault-tolerant orchestration. Through a dual-layer orchestration strategy—inter-modular and inter-agent—MAOP ensures coherent system behavior and efficient task execution in dynamic environments. The proposed architecture supports seamless interoperability with existing systems. Furthermore, it establishes a robust foundation for future advancements in optimization strategies and user interaction mechanisms.