This project is the culmination of what I have been working on in my first semester robotics class at Georgia Tech, and will be continually developed as the semester progresses.

At its current stage, I have implemented a two-state controller that processes LiDAR and odometry data in order to complete a given set of waypoints while avoiding dynamic objects placed in its environment. The algorithm is running locally on the TurtleBot3 using ROS2 and Python, built using custom proportional controllers and state estimators. This implementation passed all given unit tests with over 95% consistency.

During previous assignments in this class I implemented custom image-based object tracking using OpenCV and embedded this tracking in a ROS2 environment enabling a TurtleBot3 to safely track and follow an object of a given color.

For future work in this class I plan on implementing more complex path planning algorithms in order to traverse mazes and other obstacles. I also plan on experimenting with Simultaneous Localization and Mapping (SLAM) to improve the algorithms performance and further challenge my abilities.