Medical Supplies Drone

In our Mechanical Analysis Design class, my team of four elected to undertake the task of designing, assembling, and testing a fully functioning prototype for a medical supplies drone.

Following the rigorous DMADV Six Sigma Methodology, we methodically engineered the entire product from conception to presentation. Utilizing an Arduino UNO as our microcontroller, we ensured precise management of input/output control throughout the drone's operation.

One of our primary responsibilities involved performing accurate calculations to appropriately spec the necessary motors, battery, and ESCs (Electronic Speed Controllers) needed to achieve the desired flight capabilities. These calculations factored in considerations such as weight distribution and the desired trajectory of the drone, ensuring optimal performance.

Upon completion of the project, each member of our team received Green Belt certification, affirming our mastery of the Six Sigma methodology and our ability to deliver high-quality solutions through disciplined problem-solving and successful execution.

Machine Vision Robotic Dartboard Blaster

For our Robotics and Vision graduate course project, our team embarked on a semester-long endeavor to program an IRB 120 ABB robot to pneumatically fire a Nerf bullet at a dartboard.

Our project was multifaceted, requiring the integration of OpenCV to capture and post-process images from a standard webcam focused on the dartboard. Within the dartboard setup, three Aruco markers facilitated real-time adjustments, compensating for any shifts in the board's position, be it vertically or horizontally.

Additionally, TCP/IP (Transmission Control Protocol/Internet Protocol) played a crucial role in enabling seamless communication between the Python script and the RobotStudio virtual environment. This allowed our team to input desired parameters, such as the target pie slice (dartboard positions 1-20) and the desired multiplier (1x, 2x, or 3x), regardless of the dartboard's position. Using the photo taken and the identified location via Aruco markers, positional data was transmitted to the robot, ensuring precise alignment for an accurate shot.

Graded on our ability to land the dart accurately on a randomly generated number between 1 and 60, our team's success underscored our proficiency in leveraging advanced technologies to tackle real-world challenges in robotics and vision applications.

F-14 Variable Wing Sweep Aerodynamics

In our Aerodynamics Course, our team elected to assess and analyze the aerodynamic behavior of the variable wing sweep capability that an F-14 Tomcat possess under varying flight conditions.

The F-14's unique variable wing sweep feature was tested in both tucked and fully extended positions, with angles of attack ranging from 0 to 15 degrees. Using ANSYS Fluent, SolidWorks and 3D printed models, we compared lift forces under consistent airspeed. The experiment aimed to validate the CFD (computational fluid dynamics) results against yielded data from the FLOTEK® 1440 wind tunnel, as well as hand calculations. Pressure probes were placed along the top and bottom of the the wings and outer body of the modeled jet, capturing data for direct comparison. This comprehensive analysis sheds light on the accuracy of flow simulations in predicting aerodynamic performance being crucial for aerospace design and innovation.

Fire Fighting Robot

In our Fluid Mechanics course, we utilized principles of fluid dynamics to design and simulate a robotic system for rapid deployment from a fire truck, adhering to specific constraints.

Through detailed calculations and simulations, motors, accumulators, and other components were precisely selected to ensure the desired performance will be achieved. While the robot itself was not physically built, it was fully modeled, paving the way for seamless integration into real-world applications. This project exemplified our ability to apply theoretical knowledge to practical engineering challenges with precision and efficacy.