A CODECO Case Study and Initial Validation for Edge Orchestration of Autonomous Mobile Robots

TL;DR

This paper evaluates CODECO, a new orchestration approach for autonomous mobile robots, showing it reduces CPU usage and stabilizes communication compared to Kubernetes, with some trade-offs in memory and latency.

Contribution

It introduces and compares CODECO orchestration with Kubernetes specifically for resource-constrained mobile robots in a manufacturing setting.

Findings

CODECO reduces CPU consumption in robot orchestration.

CODECO provides more stable communication patterns.

Slight increase in pod lifecycle latency with CODECO.

Abstract

Autonomous Mobile Robots (AMRs) increasingly adopt containerized micro-services across the Edge-Cloud continuum. While Kubernetes is the de-facto orchestrator for such systems, its assumptions of stable networks, homogeneous resources, and ample compute capacity do not fully hold in mobile, resource-constrained robotic environments. This paper describes a case study on smart-manufacturing AMRs and performs an initial comparison between CODECO orchestration and standard Kubernetes using a controlled KinD environment. Metrics include pod deployment and deletion times, CPU and memory usage, and inter-pod data rates. The observed results indicate that CODECO offers reduced CPU consumption and more stable communication patterns, at the cost of modest memory overhead (10-15%) and slightly increased pod lifecycle latency due to secure overlay initialization.