In 2021, Diligent unveiled Moxi, an innovative health robot designed to assist nurses by performing material delivery tasks. This project centers on optimizing the performance of Moxi’s wireless subsystem. This subsystem is vital for Moxi's autonomous functionality, facilitating pivotal functions such as data acquisition, emergency responsiveness, and remote diagnostics. Within the demanding landscape of hospital environments, strong connectivity is very important, facilitating timely interventions and seamless collaboration among multiple robotic units.

The team seeks to design an energy-efficient digital audio amplifier that provides an output sound quality on par with an analog audio amplifier.

Team Members:

Michael Boyd
Jonas Cadena
Mitchell Jackson
Sarah Lao
Duna Areny Molne
Jacob Tomczeszyn

CASA Tutor presents “Doc Holliday”, an AI Medical Assistant Chatbot designed using an LLM, along with the collaboration of The Boeing Company. Specifically designed for the medical industry, it uses cutting-edge AI that has been fine-tuned using a large number of medical datasets to deliver accurate, current medical advice and information. Our chatbot is designed to be a dependable resource for medical professionals and to improve the educational experience for medical students.

This project focuses on employing Automatic Dependent Surveillance-Broadcast (ADS-B) data combined with machine learning techniques to enhance the prediction of aircraft arrival times at major airports. The main goal is to optimize Air Traffic Management by offering more accurate estimates of landing times. The system will utilize a mix of historical and real-time data, including weather conditions, to train predictive models.

An autonomous drone for transporting packages containing semiconductor wafers.

Team Members:

Brandon Vu
Nicholas Cagle
Noah Najvar
Patricia Sanchez Martin
Ryan Folmar
Srishaan Iyengar

Introducing our yard robot project: a sophisticated computer vision model designed to accurately identify dog feces in yard environments. You can input any image or video and get live detection shown by a box surrounding the dog feces. To test it, our solution is shown through a robot simulator. Take our algorithm and apply it to your camera, and you can see live tracking of dog feces.

Team Members:

Alexander Kita
Nishan Kumar
Nishan Pahadi
Rohan Rao
Anvit Raju

An eBike drive system incorporating Field Oriented Control to ensure a smoother ride. A feedback loop using Texas Instruments' TMAG6180 angle sensor to measure the motor’s position and phase allows the Texas Instruments C2000 microcontroller to calculate the motor’s RPM and current to decrease jerks when using the throttle. 

Team Members:

Owen Benner

Wyatt Cole

Brandon Countryman

Anshul Kumar

Brian Lee

Luis Rodriguez

Sahil Vartak

Our project seeks to deliver an effective low-voltage DC to grid-level AC conversion, promoting renewable energy integration and grid stability by bridging  the gap between low-voltage power sources like Redox Flow Batteries (RFBs) and high-voltage AC grids for enhanced energy integration. Addressing needs in energy storage and conversion, our project focuses on developing a modular and scalable inverter system that interfaces efficiently with emerging low-voltage battery technologies and Photovoltaic (PV) cells.

Team Members: 

The project addressed the challenge of passing a pre-distorted signal through a power amplifier (PA) to achieve a linearized output signal. Typically, a PA amplifies a signal’s power, but this process introduced non-linear distortions. Digital Pre-Distortion (DPD) technology was employed to pre-distort the signal in such a way that it compensated for these non-linearities when the signal passed through the PA, resulting in a linear output.

With the growing applications of technology, agricultural equipment has seen an immense surge in technological advancements in recent years. Indoor Methods of Navigation seeks to add to these technological advancements by determining the most efficient and effective range-finding method when used indoors or in areas where GPS cannot effectively track positioning. Our project focuses on “range-finding” or accurately utilizing technology to determine the distance from a sensor to a receiver.