Toolbox Release: A WiFi-Based Relative Bearing Sensor for Robotics
It provides an open-source toolbox for multi-robot localization and sensing using existing hardware, addressing a challenging incremental need in robotics.
The paper tackles the problem of robots obtaining relative bearing to each other in non-line-of-sight settings by analyzing WiFi signal phases, achieving a mean accuracy of 5.10 degrees and median localization errors of 0.5m and 0.9m in line-of-sight and non-line-of-sight environments.
This paper presents the WiFi-Sensor-for-Robotics (WSR) toolbox, an open source C++ framework. It enables robots in a team to obtain relative bearing to each other, even in non-line-of-sight (NLOS) settings which is a very challenging problem in robotics. It does so by analyzing the phase of their communicated WiFi signals as the robots traverse the environment. This capability, based on the theory developed in our prior works, is made available for the first time as an opensource tool. It is motivated by the lack of easily deployable solutions that use robots' local resources (e.g WiFi) for sensing in NLOS. This has implications for localization, ad-hoc robot networks, and security in multi-robot teams, amongst others. The toolbox is designed for distributed and online deployment on robot platforms using commodity hardware and on-board sensors. We also release datasets demonstrating its performance in NLOS and line-of-sight (LOS) settings for a multi-robot localization usecase. Empirical results show that the bearing estimation from our toolbox achieves mean accuracy of 5.10 degrees. This leads to a median error of 0.5m and 0.9m for localization in LOS and NLOS settings respectively, in a hardware deployment in an indoor office environment.