用仿真代替硬件，实现机器人间基于WiFi信号的精准方位估计。
WiFi-CSI Sensing and Bearing Estimation in Multi-Robot Systems: An Open-Source Simulation Framework
- 通过模拟WiFi信道状态信息，构建虚拟天线阵列进行方位推算。
- 在模拟与真实Turtlebot3上验证，方位估计误差接近真实设备水平。
- 开源框架支持无硬件环境下多机器人定位算法研发。
基于无线信号的多机器人系统开发与测试需依赖专用硬件（如可监测信道的WiFi收发器），但现有设备已过时，限制了应用与工具发展。本文提出一个基于Gazebo和Matlab的开源仿真框架，复现了2022年提出的WSR工具箱功能：利用WiFi信道状态信息（CSI）的幅值与相位，结合移动机器人的运动，构建虚拟天线阵列，实现机器人间的相对方位估计。该框架无需真实硬件即可生成仿真的CSI数据，模拟配备WSR的移动机器人行为，实现高精度方位估计。通过与真实Turtlebot3机器人的实验对比，仿真结果中的CSI数据与方位估计值均表现出良好一致性。所有代码与实验配置已公开于https://github.com/BrendanxP/CSI-Simulation-Framework，为无线感知算法的无硬件开发提供虚拟平台。
原文摘要 · Abstract (English)
Development and testing of multi-robot systems employing wireless signal-based sensing requires access to suitable hardware, such as channel monitoring WiFi transceivers, which can pose significant limitations. The WiFi Sensor for Robotics (WSR) toolbox, introduced by Jadhav et al. in 2022, provides a novel solution by using WiFi Channel State Information (CSI) to compute relative bearing between robots. The toolbox leverages the amplitude and phase of WiFi signals and creates virtual antenna arrays by exploiting the motion of mobile robots, eliminating the need for physical antenna arrays. However, the WSR toolbox's reliance on an obsoleting WiFi transceiver hardware has limited its operability and accessibility, hindering broader application and development of relevant tools. We present an open-source simulation framework that replicates the WSR toolbox's capabilities using Gazebo and Matlab. By simulating WiFi-CSI data collection, our framework emulates the behavior of mobile robots equipped with the WSR toolbox, enabling precise bearing estimation without physical hardware. We validate the framework through experiments with both simulated and real Turtlebot3 robots, showing a close match between the obtained CSI data and the resulting bearing estimates. This work provides a virtual environment for developing and testing WiFi-CSI-based multi-robot localization without relying on physical hardware. All code and experimental setup information are publicly available at https://github.com/BrendanxP/CSI-Simulation-Framework
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