Modeling and Validation of Quality of Control for Edge-Offloaded Collaborative Navigation
RoboticsMultiagent Systems
Summary
The authors study how wireless network delays and unreliable connections make it hard for robots to work together smoothly, especially when avoiding collisions and navigating. They improve a control framework to better handle these real-world network issues for robots. By testing on a private 5G network, they find the best ways to balance robot control and communication settings, showing that using a more reliable network policy improves performance by about 50% compared to standard methods.
Authors
Neelabhro Roy, Mikael Hammarling, Victor Nan Fernandez-Ayala, Gourav Prateek Sharma, Mani H. Dhullipalla, Dimos V. Dimarogonas, James Gross
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.