I worked with a WPI team to develop a molding process to maximize face shield production at universities with a limited number of 3D printers. The molds that I created and the molding process was shared with 17 Universities across 13 different African Countries. As 3D printers continue to make tooling, face shields can be produced every 45 minutes. The number produced every 45 minutes is proportional to the number of molds that are filled.

My current beetle weight robot Narsil, is a horizontal spinner that I designed and built while at WPI. This robot is designed to be a mini version of the Battlebots robot tombstone. The weapon is .5lbs and has a calculated tip speed of 419MPH, driven by a 500W brushless motor. The chassis is 3D printed out of a flexible elastomer. The chassis is structurally independent to the weapon. It serves as a shock absorber to protect the electronics and drive train.

IDEX is a custom designed 3D printer completed for Mechanical Engineering academic credit. The design goals for this 3D printer were to implement two independently driven print heads and a heated chamber where all control electronics are isolated from the high temperature environment. The printer is a 24V system with a 12"x12"x12" build volume. However, the frame of the printer is significantly larger than the build volume to accommodate for insulation and additional travel required in the X axis to accommodate the dual extrudes.

I was part of the Design and build team for the WPI undergraduate Battlebots team. We competed and filmed for the TV show over a two week period in Long Beach, California. Ribbot is a 250lb modular robot that was able to switch between four different weapons. I primarily worked on developing molds to create the shape of the frog. Additionally, I was responsible for the manufacturing and engineering for components of the chassis and drivetrain.

In RBE3002 my team and I utilized the Turtlebot 3 to develop path planning and SLAM algorithms using ROS. This project demonstration had two key phases, mapping and navigation. During the mapping phase our program needed to be able to discover frontiers, generate a cspace, choose a goal and then navigate to that point without human intervention. After the robot fully mapped the environment it would return to the starting point and wait for human defined navigation goals. During the demonstration a teaching assistant would drag the robot to a new position after mapping. The would force the robot to have to localize itself within the map since the odometry data was no longer reliable.

In RBE3001 I learned to develop the forward and inverse kinematic equations to control robotic arms. The final iteration of this project used computer vision in to identify objects and translate the camera position to a grid coordinate. Then we used inverse kinematics and a trajectory planning that we created to move the arm to an object or any goal location. All programming for the motion and control of the arm was completed in Matlab while the Arm ran off a nucleo board with c++ firmware. Our teams Matlab code controlled the motion of the arm and generated a live 3D plot of the arm.