Drosophila automation
Computer vision and assay software for a team-built fruit-fly research automation platform, recognized with a People's Choice Award.
Python · Computer vision · Classification · Raspberry Pi
08 / Clemson · Team robotics project
From a camera target to coordinated motion.
A camera-guided tabletop robot connecting target selection, carriage motion, and a coordinated ball release.
01 / Context
A robot has to translate an image-space target into physical motion, then coordinate a release mechanism with that motion. The interface, camera, controller, and mechanism all have to agree on what happens next.
02 / Ownership
I co-developed and helped test the team prototype. The team integrated camera-based targeting, MATLAB/Simulink control, an Arduino-driven rack-and-pinion carriage, and a servo release.
03 / Architecture
Use camera input and color/shape information to identify a target.
Translate the selected target into a carriage position.
Use closed-loop carriage control to coordinate the mechanical system.
Sequence the servo release and return behavior through the team interface and controller.
04 / Validation
Co-developed team prototype. The visual is a conceptual illustration of its camera, control, and release sequence.
05 / Perspective
Integration is a translation problem: pixels become a target, the target becomes a position, and the position becomes a timed action. Clear interfaces make the complete sequence easier to test.