Project

# Title Team Members TA Documents Sponsor
33 Table Cleaning Robot: Autonomous Elevated Surface Cleaner
Ann Luo
Bolin Pan
Yening Liu
Jason Zhang design_document1.pdf
final_paper1.pdf
grading_sheet1.pdf
photo1.png
presentation1.pptx
proposal1.pdf
video1.mp4
Team Members:
- Ann Luo (hluo12)
- Bolin Pan (bolinp2)
- Yening Liu (yeningl2)

# Problem

Cleaning tables is a repetitive and time-consuming chore that people usually do by hand. Tables often collect dust, crumbs, and spills, making regular cleaning necessary. While robots for cleaning floors are common, there aren't many options for robots designed to clean tables. The main challenges for such a robot include stopping it from falling off the table, avoiding objects like cups and plates, and making sure the surface is cleaned thoroughly.

# Solution
The Table Cleaning Robot is a small, self-operating device made to clean flat surfaces like tables. It is designed to handle challenges such as detecting edges to avoid falling, collecting dust and crumbs, and avoiding obstacles with the advanced functionality of cleaning space under objects like glasses and plates. Unlike floor-cleaning robots, this robot is built specifically for elevated surfaces, making it safe and effective. It works by using sensors to detect edges and prevent falls, rotating brushes to collect debris, and smart navigation to move around obstacles and clean the table.

# Solution Components

## Subsystem 1: Edge Detection and Fall Prevention

This part of the robot makes sure it doesn’t fall off the table. It uses sensors, like infrared or ultrasonic sensors, to detect the edge of the table. When the robot approaches the edge, the sensors send a signal to the robot’s microcontroller, which tells the wheels to stop or turn around depending on whether the robot finished cleaning. This way, the robot stays safe and doesn’t fall.


## Subsystem 2: Debris Collection

This part is responsible for cleaning the table by picking up dust, crumbs, and small messes. It may have spinning brushes underneath that sweep the dirt into a small bin or a tiny vacuum fan can also suck up finer dust. The brushes are powered by a small motor, and the bin can be removed to empty out the dirt when it’s full.\
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The robot should clean the table row by row, ensuring the coverage of the entire surface of the table.

## Subsystem 3: Obstacle Detection
This part helps the robot navigate around obstacles and interact with objects like cups or plates. It uses sensors, like ultrasonic or LiDAR sensors, to detect objects in its way. To clean the surface under the object, we propose two potential methods, The first method is to lift objects up using a robotic arm and clean the area underneath. However, this method may struggle with smooth-surface objects like glass cups which are hard to grip securely. Also, this method may only work for lightweight objects since we plan to build a portable small-sized robot. Another way is to push the objects aside, clean the exposed area, and then push the objects back to their original positions. However, a concern of this method is that the robot might push things off the table if the objects is at the edge of the table. Therefore, we may consider combining these two methods.

## Subsystem 4: Size and Portability
The robot is designed to be compact and portable, making it suitable for a wide range of table sizes and shapes. The robot should weigh no more than 2 kg to ensure easy portability and will be no more than 20 cm x 20 cm x 10 cm(L x W x H).

# Criterion For Success
1. Edge Detection and Fall Prevention: \
The robot must detect and avoid edges with 100% reliability to prevent falls.\
It should stop or turn around within 2 cm of the edge.

2. Debris Collection:\
The robot should collect at least 90% of debris in a single cleaning cycle.\
The collection bin should hold debris from at least three cleaning cycles for a 60 cm x 60 cm table.
3. Object Interaction:\
The robot should avoid obstacles as small as 5 cm in diameter and as large as 20 cm in diameter.\
It should successfully move objects weighing up to 500 grams without knocking them over.\
The navigation system should achieve a 95% success rate in avoiding obstacles and completing cleaning tasks.
4. Size and Portability:\
The robot should operate effectively on tables ranging from 60 cm x 60 cm to 120 cm x 80 cm.\
It should clean at least 90% of the table surface area, including under objects.

Resonant Cavity Field Profiler

Salaj Ganesh, Max Goin, Furkan Yazici

Resonant Cavity Field Profiler

Featured Project

# Team Members:

- Max Goin (jgoin2)

- Furkan Yazici (fyazici2)

- Salaj Ganesh (salajg2)

# Problem

We are interested in completing the project proposal submitted by Starfire for designing a device to tune Resonant Cavity Particle Accelerators. We are working with Tom Houlahan, the engineer responsible for the project, and have met with him to discuss the project already.

Resonant Cavity Particle Accelerators require fine control and characterization of their electric field to function correctly. This can be accomplished by pulling a metal bead through the cavities displacing empty volume occupied by the field, resulting in measurable changes to its operation. This is typically done manually, which is very time-consuming (can take up to 2 days).

# Solution

We intend on massively speeding up this process by designing an apparatus to automate the process using a microcontroller and stepper motor driver. This device will move the bead through all 4 cavities of the accelerator while simultaneously making measurements to estimate the current field conditions in response to the bead. This will help technicians properly tune the cavities to obtain optimum performance.

# Solution Components

## MCU:

STM32Fxxx (depending on availability)

Supplies drive signals to a stepper motor to step the metal bead through the 4 quadrants of the RF cavity. Controls a front panel to indicate the current state of the system. Communicates to an external computer to allow the user to set operating conditions and to log position and field intensity data for further analysis.

An MCU with a decent onboard ADC and DAC would be preferred to keep design complexity minimum. Otherwise, high MIPS performance isn’t critical.

## Frequency-Lock Circuitry:

Maintains a drive frequency that is equal to the resonant frequency. A series of op-amps will filter and form a control loop from output signals from the RF front end before sampling by the ADCs. 2 Op-Amps will be required for this task with no specific performance requirements.

## AC/DC Conversion & Regulation:

Takes an AC voltage(120V, 60Hz) from the wall and supplies a stable DC voltage to power MCU and motor driver. Ripple output must meet minimum specifications as stated in the selected MCU datasheet.

## Stepper Drive:

IC to control a stepper motor. There are many options available, for example, a Trinamic TMC2100. Any stepper driver with a decent resolution will work just fine. The stepper motor will not experience large loading, so the part choice can be very flexible.

## ADC/DAC:

Samples feedback signals from the RF front end and outputs the digital signal to MCU. This component may also be built into the MCU.

## Front Panel Indicator:

Displays the system's current state, most likely a couple of LEDs indicating progress/completion of tuning.

## USB Interface:

Establishes communication between the MCU and computer. This component may also be built into the MCU.

## Software:

Logs the data gathered by the MCU for future use over the USB connection. The position of the metal ball and phase shift will be recorded for analysis.

## Test Bed:

We will have a small (~ 1 foot) proof of concept accelerator for the purposes of testing. It will be supplied by Starfire with the required hardware for testing. This can be left in the lab for us to use as needed. The final demonstration will be with a full-size accelerator.

# Criterion For Success:

- Demonstrate successful field characterization within the resonant cavities on a full-sized accelerator.

- Data will be logged on a PC for later use.

- Characterization completion will be faster than current methods.

- The device would not need any input from an operator until completion.

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