Remote localization of scaled vehicles using Fiducial Markers and OpenCV in the ROS environment

Completed as the final project for course EL 2320 - Applied Estimation at KTH Royal Institute of Technology

This project was completed with partners Akanshu Mahajan and Sharang Kaul.

This project built off of the solutions for SLAM based on ArUco markers I was simultaneously developing as a Research Engineer in the KTH Smart Mobility Lab. All python nodes and launch files were developed specifically for this application, while yaml files were configured from templates. Results (plots, videos, & report) are included in project_results.

These solutions have since been updated and current applications can be found in the KTH SML svea_starter repository

Dependencies include ROS packages: svea_starter, aruco_detect, video_stream_opencv, tf2, qualisys.