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arXiv · 2008.08243

Enabling Remote Whole-Body Control with 5G Edge Computing

Huaijiang Zhu·Manali Sharma·Kai Pfeiffer·Marco Mezzavilla·Jia Shen·Sundeep Rangan·Ludovic Righetti
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Abstract

Real-world applications require light-weight, energy-efficient, fully autonomous robots. Yet, increasing autonomy 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 performance 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 communication. 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 experienced in 5G wireless links.

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Huaijiang Zhu, Manali Sharma, Kai Pfeiffer, Marco Mezzavilla, Jia Shen, Sundeep Rangan, Ludovic Righetti. 2020-08-19. Enabling Remote Whole-Body Control with 5G Edge Computing. https://arxiv.org/abs/2008.08243

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