  Edge computing processes data near its source, reducing latency and enhancing
security compared to traditional cloud computing while providing its benefits.
This paper explores edge computing for migrating an existing safety-critical
robotics use case from an onboard dedicated hardware solution. We propose an
edge robotics architecture based on Linux, Docker containers, Kubernetes, and a
local wireless area network based on the TTWiFi protocol. Inspired by previous
work on real-time cloud, we complement the architecture with a resource
management and orchestration layer to help Linux manage, and Kubernetes
orchestrate the system-wide shared resources (e.g., caches, memory bandwidth,
and network). Our architecture aims to ensure the fault-tolerant and
predictable execution of robotic applications (e.g., path planning) on the edge
while upper-bounding the end-to-end latency and ensuring the best possible
quality of service without jeopardizing safety and security.
