Project

# Title Team Members TA Documents Sponsor
70 Automatic Drum Tuner
Joey Bacino
Jonathan Fejkiel
Max Wojtowicz
Shengyan Liu proposal1.pdf
Members

Joey Bacino - jbacino2

Jonathon Fejkiel - jfejkiel2

Wojtowicz - mwojt3

Problem

Playing instruments is a pastime enjoyed by millions of people across the world. A task that almost every musician must endure before playing is tuning their respective instrument. For many this is done easily if they are of able body and have good pitch. However, turning lugs and listening for the right tune can be difficult if someone is weaker such as a child or the elderly, or if they are inexperienced in hearing perfect pitch such as a beginner.

Solution

The solution we propose is an automatic tuner for instruments that will adjust the instrument until the desired pitch is reached. We will specifically design our tuner for use on drums. The device will strike the drum, listen for the pitch, calculate how much it should either tighten or loosen the drum, and instruct a motor to do so. It will perform extra checks to ensure the drum was adjusted properly. Additionally, the mechanism will connect to a mobile app to select pitch if time permits.

Subsystem 1

Power Management System:

To have enough power for striking the tuning hammer and turning the pegs of the drums, we will utilize a power tool battery such as a Milwaukee M12 battery system. The same battery will power the microcontroller and sensors so it must be regulated to the correct voltages to ensure the safety of the components and the user as well. The power management subcircuit will have over-current and over voltage components such as fuses and diodes to ensure circuit protection. A buck converter will step the 12V supply down to the required inputs of the rest of the components.

Subsystem 2

Drum Striking Hammer:

For the motor that drives the hammer that would strike the drum, we will use a push-pull solenoid. We’re choosing a push-pull solenoid because they can provide a consistent and quick tap. Consistency is important around the entire drum, we need to make sure each strike is the same for every single hit on every single lug we would like to tune. A quick tap also allows the drum to resonate fully and not dampen the hit by leaving the hammer on the drum head. This is important because we want our pitch detection to be able to hear the purest/most dominant tone around each lug without any type of interference. Minimizing overtones will simplify our pitch detection system as we want as close to only one tone at any given time. Also, we would experiment with different materials such as rubber, wood, and felt to see which gets us the best result for our hammer.


Subsystem 3

Pitch Detection:

To detect the pitch of the drum at its current state, a microphone will begin to read the input of audio after the hammer has struck. The returned sound snippet will be recorded and the raw audio data will be converted to frequency domain data on the microcontroller. This can be done using a Fast Fourier Transform algorithm on the microcontroller. The dominant frequency will be noted as the pitch of the drum. Based on the input for the desired note, the microcontroller will then decide if the drum needs to be tightened or loosened and by what amount.

Subsystem 4

Tuning Motor Control:

For the motor that would be turning the lugs, we want to use a high-torque servo motor. High torque is a requirement for this part because when you want to tune your drum higher and higher, you need more and more torque as the drumhead provides more and more resistance against the tuning lugs. Servo motors also offer very precise control with feedback, so we could calibrate the motor to each lug and precisely determine how much the pitch changes with how much rotation.

Subsystem 5

Pitch Correctness LEDs:

The device will have LEDs that will indicate to the user if the current pitch of the drum is correct, close, or far off from the desired pitch. It will begin lighting when the drum is first struck. Every time the drum is struck after a pitch adjustment, the LEDs will display a different color so that the user will know the progress of the tuning. Green will be displayed and stay lit once the device has finished tuning to indicate to the user that they are ready to play. While the device is not in an active tuning task, the LEDs will stay lit blue to indicate a standby mode.

Criterion For Success

Our first criteria for success will be being able to accurately detect the pitch from our pitch detection system, as that will be the basis for how the two motors act. Another criteria for success will be repeatability, our system should return consistent pitch readings and tuning results across multiple tests. The second criteria is the accurate striking of the drum. This can not be too fast or slow, and must be the correct length of time. One more can be our lug-turning motor being able to accurately turn the lugs to the desired pitch without too many intermediate hammer strikes and adjustments. We also want minimal noise and interference from our motors.

Decentralized Systems for Ground & Arial Vehicles (DSGAV)

Mingda Ma, Alvin Sun, Jialiang Zhang

Featured Project

# Team Members

* Yixiao Sun (yixiaos3)

* Mingda Ma (mingdam2)

* Jialiang Zhang (jz23)

# Problem Statement

Autonomous delivery over drone networks has become one of the new trends which can save a tremendous amount of labor. However, it is very difficult to scale things up due to the inefficiency of multi-rotors collaboration especially when they are carrying payload. In order to actually have it deployed in big cities, we could take advantage of the large ground vehicle network which already exists with rideshare companies like Uber and Lyft. The roof of an automobile has plenty of spaces to hold regular size packages with magnets, and the drone network can then optimize for flight time and efficiency while factoring in ground vehicle plans. While dramatically increasing delivery coverage and efficiency, such strategy raises a challenging problem of drone docking onto moving ground vehicles.

# Solution

We aim at tackling a particular component of this project given the scope and time limitation. We will implement a decentralized multi-agent control system that involves synchronizing a ground vehicle and a drone when in close proximity. Assumptions such as knowledge of vehicle states will be made, as this project is aiming towards a proof of concepts of a core challenge to this project. However, as we progress, we aim at lifting as many of those assumptions as possible. The infrastructure of the lab, drone and ground vehicle will be provided by our kind sponsor Professor Naira Hovakimyan. When the drone approaches the target and starts to have visuals on the ground vehicle, it will automatically send a docking request through an RF module. The RF receiver on the vehicle will then automatically turn on its assistant devices such as specific LED light patterns which aids motion synchronization between ground and areo vehicles. The ground vehicle will also periodically send out locally planned paths to the drone for it to predict the ground vehicle’s trajectory a couple of seconds into the future. This prediction can help the drone to stay within close proximity to the ground vehicle by optimizing with a reference trajectory.

### The hardware components include:

Provided by Research Platforms

* A drone

* A ground vehicle

* A camera

Developed by our team

* An LED based docking indicator

* RF communication modules (xbee)

* Onboard compute and communication microprocessor (STM32F4)

* Standalone power source for RF module and processor

# Required Circuit Design

We will integrate the power source, RF communication module and the LED tracking assistant together with our microcontroller within our PCB. The circuit will also automatically trigger the tracking assistant to facilitate its further operations. This special circuit is designed particularly to demonstrate the ability for the drone to precisely track and dock onto the ground vehicle.

# Criterion for Success -- Stages

1. When the ground vehicle is moving slowly in a straight line, the drone can autonomously take off from an arbitrary location and end up following it within close proximity.

2. Drones remains in close proximity when the ground vehicle is slowly turning (or navigating arbitrarily in slow speed)

3. Drone can dock autonomously onto the ground vehicle that is moving slowly in straight line

4. Drone can dock autonomously onto the ground vehicle that is slowly turning

5. Increase the speed of the ground vehicle and successfully perform tracking and / or docking

6. Drone can pick up packages while flying synchronously to the ground vehicle

We consider project completion on stage 3. The stages after that are considered advanced features depending on actual progress.

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