ROS2框架实现多机器人系统自动组网与任务协同
ROSCell: A ROS2-Based Framework for Automated Formation and Orchestration of Multi-Robot Systems
- 基于ROS2构建可灵活组装的多机器人计算单元
- 空闲状态时相比K3s降低显著的CPU/内存/网络开销
- 适合智能制造中快速重构的动态生产场景
现代高混合低批量制造依赖灵活自适应的矩阵化生产系统，需连接异构设备并快速重构任务。为此，我们提出ROSCell，一个基于ROS2的框架，可在多种设备间构建可扩展的计算连续体。用户可将现有机器人软件封装为可部署技能，通过简单请求即可自动组建独立单元、部署技能实例并协调通信以达成任务目标。实验表明，在空闲状态下，ROSCell在边缘设备上相比K3s方案显著降低CPU、内存和网络开销，凸显其在大规模生产部署中的能效优势与成本效益。源码、示例与文档将开源至Github。
原文摘要 · Abstract (English)
Modern manufacturing under High-Mix-Low-Volume requirements increasingly relies on flexible and adaptive matrix production systems, which depend on interconnected heterogeneous devices and rapid task reconfiguration. To address these needs, we present ROSCell, a ROS2-based framework that enables the flexible formation and management of a computing continuum across various devices. ROSCell allows users to package existing robotic software as deployable skills and, with simple requests, assemble isolated cells, automatically deploy skill instances, and coordinate their communication to meet task objectives. It provides a scalable and low-overhead foundation for adaptive multi-robot computing in dynamic production environments. Experimental results show that, in the idle state, ROSCell substantially reduces CPU, memory, and network overhead compared to K3s-based solutions on edge devices, highlighting its energy efficiency and cost-effectiveness for large-scale deployment in production settings. The source code, examples, and documentation will be provided on Github.
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