Quality of Control based Resource Dimensioning for Collaborative Edge Robotics

TL;DR

This paper introduces a QoC-based resource dimensioning approach for collaborative edge robotics, optimizing wireless communication to enhance system performance and flexibility in industrial automation.

Contribution

It proposes a novel abstraction for robotic workloads based on QoC parameters and jointly optimizes system performance considering wireless communication constraints.

Findings

Relaxing delay constraints can improve QoC significantly.

Optimal resource allocation balances communication and control costs.

Wireless solutions enable more flexible and adaptive robotic coordination.

Abstract

With the increasing focus on flexible automation, which emphasizes systems capable of adapting to varied tasks and conditions, exploring future deployments of cloud and edge-based network infrastructures in robotic systems becomes crucial. This work, examines how wireless solutions could support the shift from rigid, wired setups toward more adaptive, flexible automation in industrial environments. We provide a quality of control (QoC) based abstraction for robotic workloads, parameterized on loop latency and reliability, and jointly optimize system performance. The setup involves collaborative robots working on distributed tasks, underscoring how wireless communication can enable more dynamic coordination in flexible automation systems. We use our abstraction to optimally maximize the QoC ensuring efficient operation even under varying network conditions. Additionally, our solution allocates the communication resources in time slots, optimizing the balance between communication and control costs. Our simulation results highlight that minimizing the delay in the system may not always ensure the best QoC but can lead to substantial gains in QoC if delays are sometimes relaxed, allowing more packets to be delivered reliably.