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Enabling Remote Whole-Body Control with 5G Edge Computing
Real-world applications require light-weight, energy-efficient, fully autonomous robots. Yet, increasing auton- omy is oftentimes synonymous with escalating computational requirements. It might thus be desirable to offload intensive computation—not only sensing and planning, but also low- level whole-body control—to remote servers in order to reduce on-board computational needs. Fifth Generation (5G) wireless cellular technology, with its low latency and high bandwidth capabilities, has the potential to unlock cloud-based high per- formance control of complex robots. However, state-of-the-art control algorithms for legged robots can only tolerate very low control delays, which even ultra-low latency 5G edge computing can sometimes fail to achieve. In this work, we investigate the problem of cloud-based whole-body control of legged robots over a 5G link. We propose a novel approach that consists of a standard optimization-based controller on the network edge and a local linear, approximately optimal controller that significantly reduces on-board computational needs while increasing robustness to delay and possible loss of commu- nication. Simulation experiments on humanoid balancing and walking tasks that includes a realistic 5G communication model demonstrate significant improvement of the reliability of robot locomotion under jitter and delays likely to be experienced in 5G wireless links.
@conference{Zhu2020enabling, title = {Enabling Remote Whole-Body Control with 5G Edge Computing}, booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, abstract = {Real-world applications require light-weight, energy-efficient, fully autonomous robots. Yet, increasing auton- omy is oftentimes synonymous with escalating computational requirements. It might thus be desirable to offload intensive computation—not only sensing and planning, but also low- level whole-body control—to remote servers in order to reduce on-board computational needs. Fifth Generation (5G) wireless cellular technology, with its low latency and high bandwidth capabilities, has the potential to unlock cloud-based high per- formance control of complex robots. However, state-of-the-art control algorithms for legged robots can only tolerate very low control delays, which even ultra-low latency 5G edge computing can sometimes fail to achieve. In this work, we investigate the problem of cloud-based whole-body control of legged robots over a 5G link. We propose a novel approach that consists of a standard optimization-based controller on the network edge and a local linear, approximately optimal controller that significantly reduces on-board computational needs while increasing robustness to delay and possible loss of commu- nication. Simulation experiments on humanoid balancing and walking tasks that includes a realistic 5G communication model demonstrate significant improvement of the reliability of robot locomotion under jitter and delays likely to be experienced in 5G wireless links.}, pages = {3553-3560}, publisher = {IEEE}, address = {Piscataway, NJ, USA}, month = oct, year = {2020}, slug = {zhu2020enabling}, author = {Zhu, Huaijiang and Sharma, Manali and Pfeiffer, Kai and Mezzavilla, Marco and Shen, Jia and Rangan, Sundeep and Righetti, Ludovic}, url = {https://ieeexplore.ieee.org/document/9341113}, month_numeric = {10} }