通过5G与机器人协同调度，实现15%能耗降低，延长续航时间。
Energy-aware Joint Orchestration of 5G and Robots: Experimental Testbed and Field Validation
- 融合5G与ROS，动态调度任务与传感器以优化能耗
- 实测在校园环境实现约15%的机器人能耗降低
- 适合关注边缘计算与移动机器人能效的工程师
5G移动网络为室外环境中移动机器人的连接与操作带来了新可能，借助5G的云原生与任务卸载特性，可实现全场景灵活协同的云机器人作业。然而，机器人有限的电池寿命仍是其在真实探索场景中有效应用的重大障碍。本文通过实地实验，验证了OROS——一种5G与机器人操作系统（ROS）的联合编排机制——在导航、感知及云端服务资源利用方面的协同优化能力，基于实时反馈最小化机器人端的总资源与能耗。我们在由商用现成机器人和本地部署的5G基础设施组成的实验测试平台上设计、实现并评估了该方案。实验结果表明，相比现有最优方法，该策略通过将高负载计算任务卸载至5G边缘基础设施，并对机载传感器实施动态能源管理（如无需时关闭），实现了约15%的机器人能耗节省，显著延长了电池寿命，从而支持更长时间运行与更高资源利用率。
原文摘要 · Abstract (English)
5G mobile networks introduce a new dimension for connecting and operating mobile robots in outdoor environments, leveraging cloud-native and offloading features of 5G networks to enable fully flexible and collaborative cloud robot operations. However, the limited battery life of robots remains a significant obstacle to their effective adoption in real-world exploration scenarios. This paper explores, via field experiments, the potential energy-saving gains of OROS, a joint orchestration of 5G and Robot Operating System (ROS) that coordinates multiple 5G-connected robots both in terms of navigation and sensing, as well as optimizes their cloud-native service resource utilization while minimizing total resource and energy consumption on the robots based on real-time feedback. We designed, implemented and evaluated our proposed OROS in an experimental testbed composed of commercial off-the-shelf robots and a local 5G infrastructure deployed on a campus. The experimental results demonstrated that OROS significantly outperforms state-of-the-art approaches in terms of energy savings by offloading demanding computational tasks to the 5G edge infrastructure and dynamic energy management of on-board sensors (e.g., switching them off when they are not needed). This strategy achieves approximately 15% energy savings on the robots, thereby extending battery life, which in turn allows for longer operating times and better resource utilization.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。