提出控制-通信协同设计框架，提升边缘协同导航可靠性
Modeling and Validation of Quality of Control for Edge-Offloaded Collaborative Navigation
- 构建端到端网络影响模型，分析控制参数对延迟与可靠性的耦合效应
- 实验验证显示，在特定条件下，可靠模式比尽力而为模式提升51.5%控制质量
- 适用于需要高可靠通信的机器人协同导航场景
在复杂环境中，协同导航面临随机无线延迟和可靠性波动的严峻挑战，这些网络不确定性会降低导航、跟踪和避障性能，并影响任务中的能效维持，可能导致资源过度配置。本文针对具有动态避障能力的导航系统，将质量控制（QoC）框架拓展至实际机器人模型。方法包括：(i) 建模端到端网络效应对闭环性能的影响；(ii) 系统研究不同控制参数对机器人运动与网络延迟-可靠性之间的关系；(iii) 在私有5G测试平台上，通过多种延迟、可靠性及控制配置的实验验证模型。分析表明，存在最优的控制-通信协同设计运行区间，并在真实条件下对比了标准ROS2服务质量（QoS）策略的性能，发现当设置为RELIABLE时，在某些实验条件下相比BEST-EFFORT可提升51.5%的QoC。
原文摘要 · Abstract (English)
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.
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