With the rising prominence of WiFi in common spaces, efforts have been made in the robotics community to take advantage of this fact by incorporating WiFi signal measurements in indoor SLAM (Simultaneous Localization and Mapping) systems. SLAM is essential in a wide range of applications, especially in the control of autonomous robots. This paper describes recent work in the development of WiFi-based localization and addresses the challenges currently faced in achieving WiFi-based geometric mapping. Inspired by the field of research into k-visibility, this paper presents the concept of inverse k-visibility and proposes a novel algorithm that allows robots to build a map of the free space of an unknown environment, essential for planning, navigation, and avoiding obstacles. Experiments performed in simulated and real-world environments demonstrate the effectiveness of the proposed algorithm.

翻译：随着WiFi在公共空间中的日益普及，机器人领域的研究人员尝试利用这一现象，将WiFi信号测量融入室内SLAM（同步定位与地图构建）系统中。SLAM在众多应用场景中至关重要，尤其是在自主机器人控制领域。本文介绍了基于WiFi定位技术的最新研究进展，并探讨了当前实现基于WiFi的几何映射所面临的挑战。受k-可见性研究领域的启发，本文提出了逆k-可见性的概念，并设计了一种新颖的算法，使机器人能够构建未知环境中自由空间的地图——这对于路径规划、导航及避障任务至关重要。在仿真环境与现实场景中的实验验证了该算法的有效性。