During this internship, I engineered and expanded the commercial application's functionalities, including point cloud I/O, filtering, segmentation, and more, utilizing the Point Cloud Library under the framework of NodeEditor and Qt-based GUI. I also developed a script using open-source machine learning APIs to label Deli's freight items, contributing to the creation of a learning dataset for FANUC's identification machine learning. I ended with this internship by authoring code documents, READMEs, dependencies in CMake files and drafted tutorials on creating a portable development environment on bootable devices to meet quick development needs.

This project designs and utilizes a model predictive controller to control a robot arm to wield a paddle and send a ball to a certain height by bouncing it on the paddle. Simulations are conducted to realize the project in a virtual environment. A full stack development from algorithm to hardware implementation is also performed. This research is conducted in Özay's Lab supervised by Kwesi Rutledge, Andrew Wintenberg, and Professor Necmiye Özay.

This project uses the hardware, software, and haptic interfaces in the embedded systems laboratory. It was to develop an adaptive cruise control system allowing different lab groups to interact over the network and receive both visual feedback from a computer monitor as well as haptic feedback.