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.

翻译：5G移动网络为户外环境中的移动机器人连接与操作引入了新的维度，其利用5G网络的云原生与卸载特性，实现了完全灵活且协作的云机器人操作。然而，机器人有限的电池续航能力仍然是其在现实探索场景中有效应用的主要障碍。本文通过现场实验，探讨了OROS（一种5G与机器人操作系统（ROS）的联合编排方案）在节能方面的潜在增益。该方案在导航与感知层面协调多个5G连接的机器人，同时优化其云原生服务资源利用率，并基于实时反馈最小化机器人的总资源与能耗。我们在由商用现成机器人和部署于校园的本地5G基础设施组成的实验测试平台上设计、实现并评估了所提出的OROS系统。实验结果表明，通过将高计算需求任务卸载至5G边缘基础设施，并对机载传感器（例如在不需要时将其关闭）进行动态能量管理，OROS在节能方面显著优于现有先进方法。该策略实现了机器人约15%的节能，从而延长了电池续航时间，这反过来允许更长的运行时间和更好的资源利用率。