Project

# Title Team Members TA Documents Sponsor
11 Glove Controlled Drone
Aneesh Nagalkar
Atsi Gupta
Zach Greening
Wenjing Song proposal1.pdf
Glove Controlled Drone

Team Members
- Aneesh Nagalkar (aneeshn3)
- Zach Greening (zg29)
- Atsi Gupta (atsig2)

# Problem
Controlling drones typically requires handheld remote controllers or smartphones, which may not feel natural and can limit user interaction. A more intuitive way to control drones could increase accessibility, improve user experience, and open possibilities for new applications such as training, entertainment, or assistive technology.


# Solution
Our group proposes building a wearable gesture-control glove that sends commands to a quadcopter. The glove will use motion sensors to detect the user’s hand orientation and movements, translating them into drone commands (e.g., tilting forward moves the drone forward). The glove will transmit these commands wirelessly to the quadcopter through an ESP32 Wi-Fi module. The drone will be purchased in parts to simplify integration and ensure reliable flight mechanics, while the glove will be custom-built.

To improve from previous iterations of similar projects, we plan to:
- Use IMU sensors instead of flex sensors for more precise and complex gesture detection.
- Add haptic feedback to communicate status updates to the user (e.g., low battery, weak signal).
- Implement an emergency shutoff mechanism triggered by a specific hand gesture (e.g., closing the hand).
- Potentially integrate a camera onto the quad copter that will be signalled by a different hand gesture.

The system is also scalable to include advanced commands such as speed adjustments based on motion severity.

# Solution Subsystems
**Subsystem 1: Gesture Detection**
- IMU and gyroscope sensors embedded in the glove to detect orientation and movement.
- Sensor fusion algorithms to interpret gestures into defined drone commands.

1. Three axis gyroscope: mpu-6050
2. IMU: Pololu MinIMU-9 v6
Controls:
Here is a clear definition of how the drone will move
- Drone maintains a constant hover height (handled by the drone’s onboard flight controller barometer/altimeter stabilization)
- The glove only controls horizontal motion and yaw (turning
- Pitch forward (tilt hand down): Move forward
- Pitch backward (tilt hand up): Move backward
- Roll left (tilt hand left): Strafe left
- Roll right (tilt hand right): Strafe right
- Yaw (rotate wrist clockwise/counter-clockwise): Turn left/right
- Clenched fist (or another distinct gesture): Emergency stop / shutoff

**Subsystem 2: Communication Module**
- ESP32 microcontroller on the glove acts as the transmitter.
- Wi-Fi connection to the drone for sending control signals.

1. ESP32 microcontroller
2. Integrated ESP32 wifi chip
3. Voltage regulation

**Subsystem 3: Quadcopter Hardware**
- Drone hardware purchased off-the-shelf to ensure stable flight.
- Integrated with receiver to interpret Wi-Fi commands from the glove

1. LiteWing – ESP32-Based Programmable Drone

**Subsystem 4: Feedback and Safety Enhancements**
- Haptic motors embedded in the glove to provide vibration-based feedback.
- Emergency shutoff gesture detection for immediate drone power-down.

1. Vibrating Actuator: Adafruit 10 mm Vibration Motor
2. Driver for actuator: Precision Microdrives 310-117
3. Battery: Adafruit 3.7 V 1000 mAh Li-Po
4. Glove that components will be affixed to

# Criterion for Success, minimum 5/7 of these
- The glove reliably detects and distinguishes between multiple hand movements.
- The drone responds in real time to glove commands with minimal delay.
- Basic directional commands (forward, back, left, right, up, down) work consistently.
- Scaled commands (e.g., varying speed/acceleration) function correctly.
- Haptic feedback provides clear communication of system status to the user.
- The emergency shutoff mechanism works reliably and immediately.
- The system demonstrates smooth, safe, and intuitive user control during a test flight.

Iron Man Mouse

Jeff Chang, Yayati Pahuja, Zhiyuan Yang

Featured Project

# Problem:

Being an ECE student means that there is a high chance we are gonna sit in front of a computer for the majority of the day, especially during COVID times. This situation may lead to neck and lower back issues due to a long time of sedentary lifestyle. Therefore, it would be beneficial for us to get up and stretch for a while every now and then. However, exercising for a bit may distract us from working or studying and it might take some time to refocus. To control mice using our arm movements or hand gestures would be a way to enable us to get up and work at the same time. It is similar to the movie Iron Man when Tony Stark is working but without the hologram.

# Solution Overview:

The device would have a wrist band portion that acts as the tracker of the mouse pointer (implemented by accelerometer and perhaps optical sensors). A set of 3 finger cots with gyroscope or accelerometer are attached to the wrist band. These sensors as a whole would send data to a black box device (connected to the computer by USB) via bluetooth. The box would contain circuits to compute these translational/rotational data to imitate a mouse or trackpad movements with possible custom operation. Alternatively, we could have the wristband connected to a PC by bluetooth. In this case, a device driver on the OS is needed for the project to work.

# Solution Components:

Sensors (finger cots and wrist band):

1. 3-axis accelerometer attached to the wrist band portion of the device to collect translational movement (for mouse cursor tracking)

2. gyroscope attached to 3 finger cots portion to collect angular motion when user bend their fingers in different angles (for different clicking/zoom-in/etc operations)

3. (optional) optical sensors to help with accuracy if the accelerometer is not accurate enough. We could have infrared emitters set up around the screen and optical sensors on the wristband to help pinpoint cursor location.

4. (optional) flex sensors could also be used for finger cots to perform clicks in case the gyroscope proves to be inaccurate.

Power:

Lithium-ion battery with USB charging

Transmitter component:

1. A microcontroller to pre-process the data received from the 4 sensors. It can sort of integrate and synchronize the data before transmitting it.

2. A bluetooth chip that transmits the data to either the blackbox or the PC directly.

Receiver component:

1. Plan A: A box plugged into USB-A on PC. It has a bluetooth chip to receive data from the wristband, and a microcontroller to process the data into USB human interface device signals.

2. Plan B: the wristband is directly connected to the PC and we develop a device driver on the PC to process the data.

# Criterion for Success:

1. Basic Functionalities supported (left click, right click, scroll, cursor movement)

2. Advanced Functionalities supported(zoom in/out, custom operations eg. volume control)

3. Performance (accuracy & response time)

4. Physical qualities (easy to wear, durable, and battery life)