Energy-Aware Joint Orchestration of 5G and Robots: Experimental Testbed and Field Validation
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.
Authors
- Antonio de la Oliva (ORCID: https://orcid.org/0000-0002-2510-6632)
- Lanfranco Zanzi (ORCID: https://orcid.org/0000-0002-2714-0519)
- Milan Groshev (ORCID: https://orcid.org/0000-0002-8035-7389)
- Carmen Delgado (ORCID: https://orcid.org/0000-0002-0719-7198)
- Xavier Costa‐Pérez (ORCID: https://orcid.org/0000-0002-9654-6109)
- Xi Li (ORCID: https://orcid.org/0000-0002-4331-0805)
Institutions
- Hospital La Luz (ES)
- i2CAT (ES)
- NEC (Germany) (DE)
- Universidad Carlos III de Madrid (ES)
Publication Details
- Journal
- IEEE Transactions on Network and Service Management
- Published
- 2025-03-26
- DOI
- https://doi.org/10.1109/tnsm.2025.3555126
- Citations
- 4
- Primary Topic
- Modular Robots and Swarm Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 2.85
Funders
- Horizon 2020 Framework Programme
- HORIZON EUROPE Framework Programme