Week 10

References: Quantum Coin Flip, Quantum Coin Flipping Video, Scholarship Poster, Quantum Coin Flipping (Wikipedia)

Phone Holder & Amplifier

Designed a phone holder with integrated passive amplifier for audio output. The design incorporates a spring-loaded mechanism for secure phone mounting and a horn-shaped amplifier for enhanced sound projection.

Stylus Design & Development

Developed multiple iterations of the stylus mechanism for touch screen interaction, progressing from simple manual designs to a linear actuator-driven system for precise control.

Tapping & Swiping Motor System

Designed a motor-driven system for tapping and swiping gestures using a linear actuator mechanism with servo control for precise horizontal movement.

Camera System & Edge AI Integration

Developed the camera subsystem with Wi-Fi livestreaming and edge AI inference capabilities for real-time object detection and face recognition.

Edge AI Face Detection

The Edge AI system uses a FOMO (Faster Objects, More Objects) model from Edge Impulse for real-time face detection. The model was trained on person/face classification data from the Model Zoo, converted to TensorFlow Lite format, and compiled as an Arduino library for deployment on the ESP32-S3.

The system processes camera frames through the on-device inference pipeline, outputs bounding box coordinates for detected faces, converts these coordinates to distance measurements, and sends byte packets to motor microcontroller boards for control. This enables real-time person tracking and machine interaction based on face detection.

Edge Impulse Model: View model in Edge Impulse Studio →

Development References: ChatGPT Transcript 1, ChatGPT Transcript 2, ChatGPT Transcript 3, ChatGPT Transcript 4

User Interface Design

Designed the v1 GUI for manual control and monitoring of the machine's subsystems.

Phone Holder & Amplifier

Design files for the phone holder with integrated passive amplifier.

• phone-holder-print.3mf — Main phone holder 3MF file
• phone-stand-amplifier-print.3mf — Amplifier horn 3MF file

References: Spring Loaded Phone Holder (Thingiverse), Phone Amplifier Passive Speaker (Thingiverse)

Stylus

Design files for the stylus mechanism.

• printable_stylus_with_built_in_stand.stl — Stylus with integrated stand

References: Printable Stylus (Thingiverse)

Tapping & Swiping Motors

Design files for the linear actuator and servo-driven tapping/swiping mechanism.

• linear_motor.3mf — Linear motor assembly
• linear_motor_stylus.3mf — Linear motor with stylus mount
• Case_R.3mf, Linear_Case_L.3mf — Motor case components
• Gear.3mf, Linear_Rack_RL.3mf — Gear and rack components

References: Linear MG90S Micro Servo (Thingiverse), Linear Actuator Design (Thingiverse)

Servo Motor Controls

Arduino code for controlling two MG90S servo motors for tapping and swiping mechanisms.

Vinyl Cutter Designs

Vinyl sticker designs generated using VDraw.ai black-and-white image converter for preparing artwork suitable for vinyl cutting.

• VDraw_1763512341238.png — "Swiper No Swiping" sticker design converted from original artwork
• VDraw_1763514225691.png — "Brainrot9000" logo sticker design generated from Gemini-created artwork

The VDraw.ai converter optimizes images for vinyl cutting by creating clean black-and-white designs with clear edges and minimal detail loss, ensuring successful cutting and weeding operations.

Phone Swiper & Tapper Design

Complete design for the phone holder with integrated swiper and tapper mechanisms, including servo mounts, linear actuators, and motion guides.

• phone holder and movement v8.f3z — Fusion 360 design file (v8) for phone holder with integrated swiper and tapper mechanisms

The design includes all mechanical components for the phone holder, servo-driven linear actuators for tapping and swiping, mounting brackets, and protective enclosures for reliable operation.

Speaker PCB

PCB design files for the speaker/amplifier subsystem circuit board, including Gerber files for fabrication and design documentation.

• DFPlayer-F_Cu.gbr — Front copper layer Gerber file for PCB fabrication
• DFPlayer-Edge_Cuts.gbr — Edge cuts Gerber file defining board outline
• pcb_design.png — PCB layout visualization showing component placement and trace routing
• pcb_schematic.png — Circuit schematic diagram showing electrical connections and component relationships

The PCB was milled using the Othermill machine following the standard operating procedures documented in Week 5 training documentation.

Camera System Code

Arduino code for ESP32-S3 camera livestreaming and Edge AI face detection.

SETUP:
  1. Initialize Serial communication (115200 baud)
  2. Configure camera pins (from camera_pins.h):
     - Data pins (Y2-Y9) for parallel data bus
     - Control pins (XCLK, PCLK, VSYNC, HREF)
     - I2C pins (SIOD, SIOC) for camera configuration
  3. Create camera_config_t structure:
     - Set LEDC channel and timer for clock generation
     - Map all GPIO pins to camera interface
     - Set XCLK frequency to 20MHz
     - Set pixel format to JPEG
     - Configure frame size (QVGA if PSRAM available, QQVGA otherwise)
     - Set JPEG quality to 12 (if PSRAM available)
     - Set frame buffer count (2 if PSRAM, 1 otherwise)
  4. Initialize camera with esp_camera_init()
  5. Connect to Wi-Fi network:
     - Begin connection with SSID and password
     - Wait until connection established
     - Print local IP address
  6. Start HTTP server:
     - Create HTTP server configuration
     - Register URI handler for root path "/"
     - Set handler function to stream_handler
     - Start server and print access URL

STREAM_HANDLER (HTTP request handler):
  1. Set HTTP response type to "multipart/x-mixed-replace; boundary=frame"
  2. Enter infinite loop:
     a. Capture frame from camera (esp_camera_fb_get())
     b. If capture fails, return error
     c. Format HTTP multipart header:
        - Boundary marker: "--frame"
        - Content-Type: "image/jpeg"
        - Content-Length: frame buffer length
     d. Send header chunk via HTTP response
     e. Send frame buffer data chunk
     f. Return frame buffer to camera (esp_camera_fb_return())
     g. Send boundary terminator "\r\n"
     h. If any send operation fails, break loop
  3. Return result status

LOOP:
  - Minimal delay (10ms) to allow other tasks

Edge AI Face Detection Library

Edge Impulse Arduino library for FOMO-based face detection on ESP32-S3.

• ei-face-detection--fomo-arduino-1.0.90.zip — Edge Impulse Arduino library (v1.0.90)

Edge Impulse Model: View model in Edge Impulse Studio →

Electrical Connections

Servo Control Pseudocode

SETUP:
  1. Initialize Serial communication (115200 baud)
  2. Allocate PWM timers for ESP32-S3 (timer 0 and timer 1)
  3. Attach servo1 to GPIO1 with pulse range 500-2400μs (MG90S range)
  4. Attach servo2 to GPIO2 with pulse range 500-2400μs

LOOP:
  1. Sweep forward (0° to 180°):
     - servo1: 0° → 180° (incrementing)
     - servo2: 180° → 0° (decrementing, opposite direction)
     - 10ms delay between steps
  2. Sweep backward (180° to 0°):
     - servo1: 180° → 0° (decrementing)
     - servo2: 0° → 180° (incrementing, opposite direction)
     - 10ms delay between steps
  3. Repeat continuously

SETUP:
  1. Initialize Serial communication (115200 baud)
  2. Allocate PWM timers (timer 0 and timer 1)
  3. Attach both servos to GPIO1 and GPIO2 with 500-2400μs range

MOVE_BOTH function:
  - Set both servos to same angle simultaneously
  - Wait 120ms for MG90S to reach position (tunable delay)

LOOP (4-step pattern):
  1. Move both servos to 90° (center position)
  2. Move both servos to 180° (full extension)
  3. Move both servos to 90° (return to center)
  4. Move both servos to 0° (full retraction)
  5. Repeat pattern

For complete code files, see Servo Motor Controls in Design Files.

Design Process

The vinyl designs were created using VDraw.ai black-and-white image converter to prepare artwork for vinyl cutting. Two main designs were developed:

• "Swiper No Swiping" sticker: Converted from original artwork using VDraw.ai to create a clean, cuttable design suitable for vinyl cutting.
• "Brainrot9000" logo sticker: Generated from a Gemini-created design, processed through VDraw.ai to optimize for vinyl cutting with clear edges and minimal detail loss.

Application Steps

1. Vinyl Cutting: Loaded the converted designs into the vinyl cutter software and cut the designs from colored vinyl sheets, ensuring proper blade depth and cutting speed for clean edges.
2. Weeding: Carefully removed excess vinyl material around the designs using tweezers, leaving only the desired graphic elements on the backing paper.
3. Transfer Paper Application: Applied transfer tape over the weeded vinyl design, using a squeegee to ensure proper adhesion and remove air bubbles.
4. Surface Preparation: Cleaned the target surface on the Brainrot9000 assembly to ensure proper adhesion, removing dust and oils.
5. Positioning & Application: Positioned the transfer paper with the vinyl design on the target surface, then used a squeegee to press the vinyl onto the surface, working from center to edges.
6. Transfer Paper Removal: Slowly peeled away the transfer paper at a low angle, leaving the vinyl design adhered to the surface. Applied additional pressure to any areas that didn't transfer properly.

Development Process

1. Mechanical Design: Collaborated on the design of tapper and swiper enclosures, ensuring proper servo mounting, linear motion guides, and protective casings for reliable operation.
2. Electrical Integration: Wired two MG90S servo motors to ESP32-S3 GPIO pins (GPIO1 for tapper, GPIO2 for swiper) with shared 5V power and ground connections.
3. Firmware Development: Co-developed servo control code implementing synchronized motion patterns, including opposite-direction sweeps and coordinated 4-step sequences.
4. Assembly: Assembled the tapper and swiper mechanisms, mounting servos, installing linear actuators, and securing enclosures to the machine chassis.
5. Troubleshooting: Tested motion patterns, identified and resolved timing issues, adjusted servo positions, and fine-tuned PWM signals for optimal performance.

Development Approach

1. Reference Research: Identified and shared relevant references for person detection, face tracking, and camera control algorithms suitable for the ESP32-S3 platform.
2. Code Logic Design: Collaborated on the overall architecture, discussing how to integrate Edge AI face detection with motor control for following behavior.
3. Implementation Support: Provided code examples from references and developed custom implementations for bounding box processing, distance calculation, and motor control mapping.
4. Problem Solving: Worked through issues including camera frame rate optimization, detection accuracy, motor response timing, and coordinate system mapping.
5. Team Collaboration: Coordinated with other programmers to integrate the person follower with the overall machine control system and ensure proper communication between subsystems.

Integration Steps

1. Subsystem Coordination: Worked with teams responsible for camera, display, and control systems to establish communication protocols and timing requirements.
2. Electrical Integration: Consolidated wiring for all actuation systems, ensuring proper power distribution and signal routing throughout the machine chassis.
3. Software Integration: Integrated servo control code with the main machine control loop, ensuring proper sequencing and coordination between different automation functions.
4. Testing & Validation: Performed end-to-end tests of the complete actuation system, verifying that all subsystems work together without conflicts or timing issues.
5. Calibration: Fine-tuned motion parameters, timing delays, and control thresholds to optimize the overall system performance.

Assembly Process

1. Component Layout: Organized camera module, display screen, and control boards within the head enclosure, ensuring proper spacing and cable management.
2. Mechanical Mounting: Secured all components using appropriate fasteners and mounting brackets, ensuring stability and proper alignment.
3. Electrical Connections: Routed and connected all cables for power, data, and control signals, using cable management solutions to prevent interference and tangling.
4. Integration Testing: Tested the head subsystem independently to verify all components function correctly before integration with the main chassis.
5. Cross-Subsystem Integration: Worked with other teams to connect the head subsystem to the main machine body, ensuring proper mechanical and electrical interfaces.

Final Assembly Steps

1. Chassis Integration: Mounted the head subsystem, tapper/swiper mechanisms, and base components onto the main machine chassis, ensuring proper alignment and structural integrity.
2. Electrical Consolidation: Connected all subsystem wiring to the main power distribution and control boards, implementing proper cable management throughout the assembly.
3. Software Integration: Integrated all subsystem control code into the main machine control loop, ensuring proper communication and coordination between all automated functions.
4. System Calibration: Calibrated all sensors, actuators, and control parameters to ensure optimal performance across all subsystems.
5. Final Testing: Performed comprehensive end-to-end system tests, verifying that all automation features work correctly together and that the machine operates as designed.
6. Visual Finishing: Applied vinyl stickers and completed final aesthetic touches to enhance the machine's visual presentation.

PCB Design

For complete design files including Gerber files for fabrication, see Speaker PCB in Design Files.

PCB Milling Process

1. Design Preparation: Prepared the PCB design files with proper trace routing, component footprints, and drill holes for the speaker circuit. Exported Gerber files (F_Cu for front copper layer, Edge_Cuts for board outline) for the Othermill machine.
2. Material Setup: Secured the FR-1 copper-clad board to the milling machine bed using double-sided tape, ensuring proper leveling and flatness for accurate milling. Positioned the board left-justified with 1mm buffer from origin.
3. Tool Selection: Selected appropriate end mills (1/64" for trace isolation, 1/32" for drilling) following the Othermill standard operating procedures, considering trace width and spacing requirements.
4. Milling Execution: Ran the milling program using Bantam Tools software to isolate traces, create pads, and drill component mounting holes with precise depth control. Monitored the process to ensure proper tool engagement and material removal.
5. Quality Inspection: Inspected the milled PCB for trace continuity, proper isolation, and clean edges before component assembly. Checked for stray copper strands and addressed any issues with light sanding or utility knife.
6. Component Assembly: Soldered components to the milled PCB, including audio connectors, signal routing components, and interface connections, following proper soldering techniques for reliable electrical connections.