This paper introduces an expanded Quality of Control (QoC) framework to address challenges in collaborative robotic navigation caused by unreliable wireless networks. The research models the end-to-end impact of network conditions on closed-loop performance and explores how control parameters affect latency and reliability. Experimental validation on a private 5G testbed demonstrates that the RELIABLE Quality of Service (QoS) policy in ROS 2 can improve QoC by 51.5% compared to best-effort delivery under specific conditions. AI
IMPACT This research could lead to more robust and efficient collaborative navigation systems for autonomous robots in challenging network environments.
RANK_REASON This is a research paper detailing a new framework and experimental validation for robotic control systems. [lever_c_demoted from research: ic=1 ai=0.7]
Read on arXiv cs.MA (Multiagent) →
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