Comparison between Docker and Kubernetes based Edge Architectures for Enabling Remote Model Predictive Control for Aerial Robots

TL;DR

This paper compares Docker and Kubernetes-based edge architectures for remote model predictive control of UAVs, evaluating their efficiency through simulations to determine suitability for robotic applications.

Contribution

It introduces and compares two edge architectures for UAV control using Docker and Kubernetes within the ROS framework, providing insights into their performance.

Findings

Docker-based architecture shows lower latency in simulations.

Kubernetes architecture offers better scalability.

Both architectures effectively enable remote UAV control.

Abstract

Edge computing is becoming more and more popular among researchers who seek to take advantage of the edge resources and the minimal time delays, in order to run their robotic applications more efficiently. Recently, many edge architectures have been proposed, each of them having their advantages and disadvantages, depending on each application. In this work, we present two different edge architectures for controlling the trajectory of an Unmanned Aerial Vehicle (UAV). The first architecture is based on docker containers and the second one is based on kubernetes, while the main framework for operating the robot is the Robotic Operating System (ROS). The efficiency of the overall proposed scheme is being evaluated through extended simulations for comparing the two architectures and the overall results obtained.