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This paper expands the quality of control (QoC) framework to address the challenges of collaborative navigation in environments affected by stochastic wireless delays and reliability issues. By modeling the end-to-end network effects on robotic performance and systematically exploring control parameters, the authors validate their findings through experiments on a private 5G testbed. The results reveal that the RELIABLE quality of service (QoS) policy significantly enhances QoC by 51.5% compared to the BEST-EFFORT policy under specific conditions, highlighting the importance of control-communication co-design in practical robotic applications.
RELIABLE QoS can boost robotic navigation performance by over 51% compared to BEST-EFFORT, revealing critical insights for real-world applications.
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.
