{"ID":2843468,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.08354","arxiv_id":"2511.08354","title":"A CODECO Case Study and Initial Validation for Edge Orchestration of Autonomous Mobile Robots","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.","short_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...","url_abs":"https://arxiv.org/abs/2511.08354","url_pdf":"https://arxiv.org/pdf/2511.08354v1","authors":"[\"H. Zhu\",\"T. Samizadeh\",\"R. C. Sofia\"]","published":"2025-11-11T15:31:38Z","proceeding":"cs.RO","tasks":"[\"cs.RO\",\"cs.ET\",\"cs.NI\"]","methods":"[]","has_code":false}