Demo：基于ROS 2的无线感知机器人导航的闭环Sionna-Isaac Sim联合仿真框架
Demo: Closed-Loop Sionna-Isaac Sim Co-Simulation Framework for Wireless-Aware Robot Navigation over ROS 2
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- Singapore University of Technology and Design（新加坡科技设计大学）
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中文总结 AI 辅助
提出一个基于ROS 2的实时闭环联合仿真框架，耦合Isaac Sim与Sionna，实现无线感知导航，在SUTD校园孪生环境中验证，仅增加7.4%通行时间即消除通信中断。
中文摘要 AI 辅助
一个将控制回路卸载到网络的机器人会随身携带接收器，因此链路质量取决于其行进位置。对此进行仿真需要同时使用物理引擎和特定地点的传播模型；据我们所知，目前没有仿真器能原生统一两者，现有的两者耦合仅限于离线分析。我们演示了一个通过ROS 2耦合NVIDIA Isaac Sim和NVIDIA Sionna的实时联合仿真框架，该框架闭合了二者之间的感知-行动-通信（PAC）回路。Sionna基于Isaac Sim模拟的确切几何形状，对基站到机器人的信道进行光线追踪，而非随机建模，并实时将信道状态反馈到控制回路中。在GPU上进行光线追踪，覆盖图约在16毫秒（约60赫兹）内刷新，足以满足实时控制需求。为展示该框架的实用性，我们在一个源自OpenStreetMap（OSM）的新加坡科技设计大学（SUTD）校园孪生环境中，使用两台Nova Carter机器人实现了一个无线感知导航应用：闭环规划器仅以比最短路径基线多7.4%的通行时间（该基线在81.2秒的运行中有7.9秒处于断开状态）消除了通信中断。
英文摘要
A robot that offloads its control loop to the network carries the receiver with it, so link quality is decided by where it goes. Simulating this requires both a physics engine and a site-specific propagation model at once; to our knowledge no simulator natively unifies both, with existing couplings of the two limited to offline analyses. We demonstrate a real-time co-simulation framework coupling NVIDIA Isaac Sim and NVIDIA Sionna over ROS 2 that closes the perception-action-communication (PAC) loop between them. Sionna ray-traces the base-station-to-robot channel over the exact geometry Isaac Sim simulates on, rather than modeling it stochastically, and feeds channel states back into the control loop in real time. Ray-traced on GPU, the coverage map is refreshed in ~16ms (~60 Hz), fast enough for real-time control. To showcase the framework's utility, we implement a wireless-aware navigation application in an OpenStreetMap(OSM)-derived SUTD campus twin with two Nova Carter robots: the closed-loop planner eliminates communication outage at only +7.4% traversal time over the shortest-path baseline (which spends 7.9 s of its 81.2 s run disconnected).
