The project focuses on developing a methodology for monitoring bearing conditions. It combines Poincare Maps, Fast Fourier Transform (FFT), and Convolutional Neural Networks (CNN) to diagnose faults and predict the Remaining Useful Life (RUL) of bearings. 

For a Research Project course in the Automated Driving department, we are working on "Visual Lane Following for Scaled Automated Vehicles". The vehicle is based on the NVIDIA-backed open-source JetRacer platform, including an NVIDIA Jetson Nano. Specifically, I am working on lane detection using classical and deep learning techniques.

As part of the graduate-level Mechanisms and Robotics course, I led a team of four students to develop an Apple Fruit Picker robot. We modeled the robot using SolidWorks and created animations in Blender. MATLAB and Python were employed to compute the robot's Forward and Inverse Kinematics and Dynamics.