Project

# Title Team Members TA Documents Sponsor
34 Board Buddy
 Alfredo Angel
Gabe Valles
Louie Conn
 Surya Vasanth proposal1.pdf
# Board Buddy

## Team Members:
- Alfredo Angel (alfredo9)
- Gabriel Valles (gvall4)
- Lewis Conn (lewisc2)

# Problem

Instructional writing boards, such as chalkboards and whiteboards, are widely used in educational and professional settings, but manually erasing these boards is time-consuming and disrupts workflow. During brainstorming sessions, lectures, or meetings, manually erasing the board can slow down productivity. Additionally, custodians spend hours cleaning boards outside of school hours, making it a labor-intensive task. Current solutions are either completely manual or require expensive, rail-based automated systems that only work on pre-sized boards.

There is a need for a cost-effective, portable, and efficient automated eraser that can remotely clean boards of various sizes and shapes with minimal human intervention.

# Solution

We propose **BoardBuddy**, an autonomous board eraser designed to clean magnetic writing boards efficiently. The device will attach securely using **neodymium magnets** and navigate using **omnidirectional wheels** controlled by an **ESP32 microcontroller**. It will feature **edge detection using microswitch lever arms** and **an accelerometer for stability**.

The system will be battery-powered with a **low dropout regulator (LDO)** for stable operation. It will include a **lightweight 3D-printed housing** for structural support and protection. Additionally, a **mobile application** will allow users to remotely activate the device, schedule cleaning sessions, and monitor its status.

# Solution Components

## Subsystem 1: Locomotion and Mounting

**Function:** Enables the device to move smoothly across the board while maintaining consistent contact for effective erasing.

**Components:**
- **Omnidirectional Wheels** – Allow unrestricted movement in any direction.
- **Neodymium Magnets** – Securely mount the device while allowing mobility.
- **DC Motors** – High-torque motors for smooth movement (e.g., **Pololu 25D Metal Gearmotor 12V**).
- **Motor Drivers** – Dual-channel motor drivers (e.g., **TB6612FNG**).

## Subsystem 2: Erasing Mechanism

**Function:** Erases the board as the device moves.

**Components:**
- **Eraser Pads** – Replaceable pads mounted on the device.
- **Spring Mechanism** – Ensures even pressure for effective cleaning.

## Subsystem 3: Navigation and Edge Detection

**Function:** Prevents the device from falling off the board by detecting edges and obstacles.

**Components:**
- **Microswitch Lever Arms** – Detect board edges and trigger direction changes.
- **ESP32 Microcontroller** – Processes sensor inputs and controls movement.
- **IMU Sensor (Optional, e.g., MPU-6050)** – Provides additional orientation data.

## Subsystem 4: Power Management

**Function:** Supplies stable power to all components.

**Components:**
- **LiPo Battery Pack** – Rechargeable power source.
- **LDO Voltage Regulator (e.g., LM7805)** – Steps down battery voltage for ESP32 and other components.

## Subsystem 5: Enclosure

**Function:** Protects components and provides a lightweight, compact structure.

**Components:**
- **3D-Printed Housing** – Custom enclosure for durability and heat dissipation.

## Subsystem 6: PCB Design

**Function:** Integrates motor control, edge detection, and power management into a single, compact PCB.

**Components:**
- **Custom PCB** with footprints for:
- **ESP32**
- **Motor Driver ICs (TB6612FNG)**
- **Voltage Regulator (LM7805)**
- **Edge detection circuitry (microswitch connectors)**
- **Standard connectors for battery, motors, and sensors**

## Subsystem 7: Application

**Function:** Provides remote control, scheduling, and monitoring features.

**Features:**
- **Remote Activation** of the eraser.
- **Scheduled Cleaning Sessions** (e.g., set to clean at night or after class).
- **Manual Control** via app.
- **Usage History/Log** for tracking.
- **Status Monitoring** (Idle, Cleaning, Error).
- **Developed using Flutter or React Native** for cross-platform compatibility.

# Criterion for Success

BoardBuddy will be considered successful if it meets the following criteria:

- **Effective Erasing:** Cleans most of residue in a single pass.
- **Secure Mounting:** Neodymium magnets must hold the device firmly on the board without slipping.
- **Edge Detection:** The device must detect board edges and avoid falling off.
- **Smooth Locomotion:** Omnidirectional wheels must provide **consistent and unrestricted movement**.
- **Reliable Power:** The battery must provide **at least 30 minutes of continuous operation**.
- **Compact Design:** The device must be lightweight and compact to minimize magnet usage.
- **Custom PCB Functionality:** The PCB must integrate motor control, edge detection, and power management without external breadboards or components.
- **Application Integration:** The app must allow for **remote control, scheduling, and monitoring**.

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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