Project

# Title Team Members TA Documents Sponsor
32 Air Hockey Playing Robot
 Matthew Feder
Micah Wehler
Rohan Kapur
 Lukas Dumasius
# Air Hockey Playing Robot

Team Members:
- Rohan Kapur (rohan21)
- Micah Wehler (mwehler2)
- Matthew Feder (msfeder2)

# Problem

Air hockey requires players to track and react to a fast moving object in real time, making it a challenging robotics problem. To solve this, we aim to build a robotic opponent which can autonomously move a paddle to defend and return shots against a human on a mini air hockey table.

# Solution

Our design will use an overhead camera to track the position of the puck in real time, a raspberry pi for image processing and computation, and a paddle mounted on a H-bot belted mechanism to move. This involves two main subsystems, perception and actuation.

# Solution Components

## Subsystem 1: Perception

This subsystem will track the position of the puck in real time and determine the ideal intercept location. It will use an overhead mounted Raspberry Pi Camera Module, which will be recording at 720p 120fps. These frames will then be parsed by the Raspberry Pi Compute Module 5, which will be integrated into our custom PCB. The Raspberry Pi will use a color thresholding algorithm to determine the location of the puck, and track it across frames to determine velocity and direction. This information will then be parsed by a simple physics model to determine the ideal intercept location which requires the paddle to move the minimum distance.

## Subsystem 2: Actuation

This subsystem is responsible for moving the paddle to the intercept location. It will use two NEMA 17 stepper motors, driven by TMC5160A motor drivers in our PCB, and controlled using SPI by the Compute Module. The stepper motors will drive a linear belt along a H-Bot mechanism to give the paddle two degrees of freedom while keeping both the motors stationary. This allows for rapid acceleration with fewer moving parts.

# Criterion For Success

The project should be able to contact at least 75% of incoming straight shots and 50% of the single bounce shots where the puck is traveling at less than 4 m/s.

STRE&M: Automated Urinalysis (Pitched Project)

Gage Gulley, Adrian Jimenez, Yichi Zhang

STRE&M: Automated Urinalysis (Pitched Project)

Featured Project

Team Members:

- Gage Gulley (ggulley2)

- Adrian Jimenez (adrianj2)

- Yichi Zhang (yichi7)

The STRE&M: Automated Urinalysis project was pitched by Mukul Govande and Ryan Monjazeb in conjunction with the Carle Illinois College of Medicine.

#Problem:

Urine tests are critical tools used in medicine to detect and manage chronic diseases. These tests are often over the span of 24 hours and require a patient to collect their own sample and return it to a lab. With this inconvenience in current procedures, many patients do not get tested often, which makes it difficult for care providers to catch illnesses quickly.

The tedious process of going to a lab for urinalysis creates a demand for an “all-in-one” automated system capable of performing this urinalysis, and this is where the STRE&M device comes in. The current prototype is capable of collecting a sample and pushing it to a viewing window. However, once it gets to the viewing window there is currently not an automated way to analyze the sample without manually looking through a microscope, which greatly reduces throughput. Our challenge is to find a way to automate the data collection from a sample and provide an interface for a medical professional to view the results.

# Solution

Our solution is to build an imaging system with integrated microscopy and absorption spectroscopy that is capable of transferring the captured images to a server. When the sample is collected through the initial prototype our device will magnify and capture the sample as well as utilize an absorbance sensor to identify and quantify the casts, bacteria, and cells that are in the sample. These images will then be transferred and uploaded to a server for analysis. We will then integrate our device into the existing prototype.

# Solution Components

## Subsystem1 (Light Source)

We will use a light source that can vary its wavelengths from 190-400 nm with a sampling interval of 5 nm to allow for spectroscopy analysis of the urine sample.

## Subsystem2 (Digital Microscope)

This subsystem will consist of a compact microscope with auto-focus, at least 100x magnification, and have a digital shutter trigger.

## Subsystem3 (Absorbance Sensor)

To get the spectroscopy analysis, we also need to have an absorbance sensor to collect the light that passes through the urine sample. Therefore, an absorbance sensor is installed right behind the light source to get the spectrum of the urine sample.

## Subsystem4 (Control Unit)

The control system will consist of a microcontroller. The microcontroller will be able to get data from the microscope and the absorbance sensor and send data to the server. We will also write code for the microcontroller to control the light source. ESP32-S3-WROOM-1 will be used as our microcontroller since it has a built-in WIFI module.

## Subsystem5 (Power system)

The power system is mainly used to power the microcontroller. A 9-V battery will be used to power the microcontroller.

# Criterion For Success

- The overall project can be integrated into the existing STRE&M prototype.

- There should be wireless transfer of images and data to a user-interface (either phone or computer) for interpretation

- The system should be housed in a water-resistant covering with dimensions less than 6 x 4 x 4 inches

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