- Team Leadership: Led and coordinated an 8-person team, assigning roles across perception, controls, and hardware integration.
- Computer Vision: Implemented ML-based detection and classification of bottles.
- Robotic Manipulation: Programmed the UR5 to perform real-time pick-and-place from a moving conveyor.
- Competition Performance: Achieved reliable sorting under timed conditions, with accuracy and speed that ranked among the top systems in our section.
During my sophomore spring at MIT, I took 2.12: Introduction to Robotics, taught by Professor Harry Asada. The class started with fundamentals—kinematics, electronics, and dynamics of robotic systems—and transitioned into machine learning and computer vision in the second half of the course.
The class concluded with two challenges: a mobile robot course and a UR5 pick-and-place competition. For my lab section, I served as Team Lead, guiding a group of 8 students working on the UR5 robot.
Project Theme
The theme of our year was plastic pollution clean-up. The UR5 was tasked with detecting plastic bottles moving along a conveyor belt, classifying them with computer vision, and then sorting them into the correct bins—either through precise placement or even throwing.
Project Outcomes
- Team Leadership: Led and coordinated an 8-person team, assigning roles across perception, controls, and hardware integration.
- Computer Vision: Implemented ML-based detection and classification of bottles
- Robotic Manipulation: Programmed the UR5 to perform real-time pick-and-place with a moving conveyor
- Competition Performance: Achieved reliable sorting in lab conditions, with consistent accuracy while throwing