Cloud-Assisted Remote Control for Aerial Robots: From Theory to Proof-of-Concept Implementation

2025-09-04

AI Summary

To address critical challenges—including network latency, security, and resource coordination—in cloud robotic systems, this paper proposes a containerized cloud-edge collaborative framework, validated via UAV remote control simulation. The framework establishes bidirectional, low-overhead communication between the cloud platform and the Gazebo simulation environment using UDP tunneling, and integrates Linux *tc* to dynamically emulate configurable network latency, jitter, and packet loss—ensuring experimental reproducibility. Innovatively, it tightly couples a Kubernetes container cluster with the robot simulation environment, enabling elastic scaling and cross-domain resource orchestration. Experimental results demonstrate stable closed-loop control performance under end-to-end latency ≤200 ms, validating the framework’s communication robustness and real-time capability in highly dynamic network conditions. This work provides a scalable, experimentally verifiable infrastructure for cloud-native robotic systems.

Technology Category

• Intelligent Robots: Multi-Robot Systems
• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Natural Language Processing: Safety and Robustness

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Cloud, edge and content delivery systems for the Web
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

Cloud robotics has emerged as a promising technology for robotics applications due to its advantages of offloading computationally intensive tasks, facilitating data sharing, and enhancing robot coordination. However, integrating cloud computing with robotics remains a complex challenge due to network latency, security concerns, and the need for efficient resource management. In this work, we present a scalable and intuitive framework for testing cloud and edge robotic systems. The framework consists of two main components enabled by containerized technology: (a) a containerized cloud cluster and (b) the containerized robot simulation environment. The system incorporates two endpoints of a User Datagram Protocol (UDP) tunnel, enabling bidirectional communication between the cloud cluster container and the robot simulation environment, while simulating realistic network conditions. To achieve this, we consider the use case of cloud-assisted remote control for aerial robots, while utilizing Linux-based traffic control to introduce artificial delay and jitter, replicating variable network conditions encountered in practical cloud-robot deployments.

Problem

• Integrating cloud computing with robotics faces network latency
• Security concerns challenge cloud-robot system implementations
• Efficient resource management needed for cloud robotics

Innovation

• Containerized cloud and robot simulation framework
• UDP tunnel for bidirectional cloud-robot communication
• Linux traffic control simulates realistic network conditions