Modeling and Validation of Quality of Control for Edge-Offloaded Collaborative Navigation

2026-07-16

AI Summary

This study addresses the degradation of control performance and inefficient resource utilization in cooperative robotic navigation under complex environments, where wireless latency and fluctuating communication reliability significantly impair system efficacy. For the first time, a Quality of Control (QoC) framework is extended to real-world multi-robot navigation systems, employing closed-loop control modeling to quantitatively assess the impact of network effects on control performance and systematically analyze the coupling between control parameters and communication Quality of Service (QoS). Leveraging a private 5G testbed and empirical evaluations of diverse ROS 2 QoS policies, the work identifies an operational regime for joint control-communication optimization. Experimental results demonstrate that, in representative scenarios, the RELIABLE QoS policy improves QoC by up to 51.5% compared to BEST_EFFORT, offering a principled basis for optimal cooperative configuration in practical robotic systems.

Abstract

Collaborative control in complex environments is severely challenged by stochastic wireless delay and reliability variations, which can degrade navigation, tracking, and collision avoidance. These network-induced uncertainties complicate the maintenance of energy efficiency during collaborative tasks, and can potentially lead to over-provisioning of resources. In this paper, for a navigation setup with dynamic collision avoidance, we address this challenge by expanding the quality of control (QoC) framework from prior works to practical robotic models. Our approach (i) models end-to-end network effects on closed-loop performance, (ii) systematically explores the impact of various control parameters dictating robotic motion on network latency-reliability (iii) validates these models through experiments on a private 5G testbed across varying delay, reliability and control configurations. Our analysis indicates the optimal control-communication co-design operating regimes for practical robots and also compares the QoC performance of standard ROS~2 quality of service (QoS) policies under real-world conditions and showing how RELIABLE QoS offers 51.5% better QoC than BEST-EFFORT under certain experimental settings.

Problem

• collaborative navigation
• wireless delay
• reliability variations
• quality of control
• resource over-provisioning

Innovation

• Quality of Control
• Edge Offloading
• Collaborative Navigation
• 5G Testbed
• ROS 2 QoS