PURM Project Summary
This summer I worked in the Real-time and Embedded Systems Lab (mLab) on the Autonomous Vehicles team under the mentorship of Dr. Rahul Mangharam. The team conducts research using the F1/10 platform, a safe and affordable way of testing autonomous vehicles. The vehicles have all the features of real autonomous vehicles including a LIDAR, depth camera and a full software stack, but they are one tenth the scale. During my time in the lab, I worked on streamlining the process of capturing real racetracks and cars in simulation.
I started out learning my way around the cars’ hardware. Replacing parts, modelling camera mounts, and designing a new baseplate gave me a good mechanical foundation for working with the cars. From there, I learned how to use ROS—or Robot Operating System—to operate the cars and develop new software. Using AprilTags mounted to the tops of the cars, I was able to track the cars’ poses using an overhead camera. I also created an algorithm for extracting the centerline, track walls, and signed-distance field from racetrack maps. Lastly, I learned the importance of presentation—even in the technical world of engineering; throughout the summer, I updated my co-workers by giving demonstrations of my progress as well as weekly blog posts.
Overall, this summer has been a tremendous educational experience for me. As a computer science student with aspirations for machine learning research, this opportunity sharpened my skills and gave me valuable experience in a very relevant field.
PURM Project Summary
This summer I worked in the Real-time and Embedded Systems Lab (mLab) on the Autonomous Vehicles team under the mentorship of Dr. Rahul Mangharam. The team conducts research using the F1/10 platform, a safe and affordable way of testing autonomous vehicles. The vehicles have all the features of real autonomous vehicles including a LIDAR, depth camera and a full software stack, but they are one tenth the scale. During my time in the lab, I worked on streamlining the process of capturing real racetracks and cars in simulation.
I started out learning my way around the cars’ hardware. Replacing parts, modelling camera mounts, and designing a new baseplate gave me a good mechanical foundation for working with the cars. From there, I learned how to use ROS—or Robot Operating System—to operate the cars and develop new software. Using AprilTags mounted to the tops of the cars, I was able to track the cars’ poses using an overhead camera. I also created an algorithm for extracting the centerline, track walls, and signed-distance field from racetrack maps. Lastly, I learned the importance of presentation—even in the technical world of engineering; throughout the summer, I updated my co-workers by giving demonstrations of my progress as well as weekly blog posts.
Overall, this summer has been a tremendous educational experience for me. As a computer science student with aspirations for machine learning research, this opportunity sharpened my skills and gave me valuable experience in a very relevant field.