  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.
