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ros-wifi-localization

Wireless signal strength based localization for ROS

Installation

clone this git repository and add it to your catkin path:

git clone https://github.com/RMiyagusuku/ros-wifi-localization.git /tmp/ros-wifi

Copy rss and tests to your catkin folder

scp -r /tmp/ros-wifi/rss   ~/catkin_ws/src/rss
scp -r /tmp/ros-wifi/tests ~/catkin_ws/src/tests

Rosbags for testing available at

http://www.robot.t.u-tokyo.ac.jp/~miyagusuku/datasets

Unzip and copy downloaded or original rosbags to

~/catkin_ws/src/tests/bags

Tested Platform

Ubuntu 14.04.5
ROS indigo
Python 2.7

Libraries dependencies

wifi-localization at https://github.com/RMiyagusuku/wifi-localization
GPy at https://github.com/SheffieldML/GPy
Numpy 1.11.1+
Scipy 0.18.0+

Related publications:

Renato Miyagusuku, Atsushi Yamashita and Hajime Asama: "Data Information Fusion from Multiple Access Points for WiFi-based Self-localization", IEEE Robotics and Automation Letters, Vol. 4, No. 2, pp. 269-276, April 2019. [doi:10.1109/LRA.2018.2885583]
Renato Miyagusuku, Atsushi Yamashita and Hajime Asama:"Precise and accurate wireless signal strength mappings using Gaussian processes and path loss models", Robotics and Autonomous Systems, February 2018. [doi:10.1016/j.robot.2018.02.011]
Renato Miyagusuku, Atsushi Yamashita and Hajime Asama: "Gaussian Processes Mappings Improvements Using Path Loss Models for Wireless Signals-based Localization", in: IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016, pp. 4610-4615. [doi:10.1109/IROS.2016.7759678]
* This work employs a previous python implementation available here

Maybe also of interest

WLRF: WiFi and range data fusion
Main implementations for fusing WiFi and range data: Modified amcl, wlrf ROS package
How to generate additional rosbags for testing global localization and the kidnapped robot problem can be found here

Renato Miyagusuku, Yiploon Seow, Atsushi Yamashita and Hajime Asama: "Fast and Robust Localization using Laser Rangefinder and WiFi Data", in: IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, 2017, pp. 111-117. [doi:10.1109/MFI.2017.8170415]

Questions

Please mail directly to

miyagusuku at robot.t.u-tokyo.ac.jp