Welcome to the repository for the SENTRY NERF Turret, an advanced educational mechatronics platform developed for robotics experimentation, controls engineering, and hands-on learning.
This project demonstrates how mechanical, electrical, and software systems come together in a real, fully functional robotic turret. It provides students and researchers with an accessible platform to explore feedback control, sensor fusion, actuation, and system integration — using NERF balls as the medium for experimentation.
The SENTRY turret is a fully automated NERF blaster mounted on a 2-axis pan/tilt head, controlled by a Raspberry Pi Pico running MicroPython.
The system integrates sensors, encoders, and current monitoring to deliver closed-loop control, ball detection, and real-time feedback. A custom breakout board centralizes the I²C architecture and provides additional ADC channels, making SENTRY a modular, expandable, and classroom-ready platform.
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Automated Targeting and Firing
- Dual flywheels for ball launching
- AS5600 encoder-driven feed belt for reliable ball delivery
- INA260 current-spike detection for ball counting
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Feedback & Control
- BNO055 IMU for orientation and automatic tilt leveling
- VL53L4CX Time-of-Flight (ToF) sensor for range measurement
- QRD1114 optical sensors relocated to flywheels for rotational speed measurement
- TCND5000 optical sensors to detect ball launch and calculate speed of ball
- INA260 current monitoring for real-time performance feedback
- ADS1115 I²C ADC breakout for expanded analog inputs
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Interactive System
- Push-button control for manual firing
- WS2812B RGB LEDs for real-time visual status and diagnostics
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Modular & Expandable
- Unified I²C bus for all sensors, routed through a custom breakout board
- UART communication ready for integration with a Raspberry Pi 4B and Oak-D Lite camera for advanced vision-based tracking
- Designed for educational labs, adaptable for both controls and robotics research
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Mechanical Base
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Controller
- Raspberry Pi Pico running MicroPython
- Custom breakout board consolidating I²C and ADC expansion
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Motors
- Flywheel motor (MOSFET-controlled)
- Feed belt motor with quadrature encoder
- Pan & tilt motors driven by BD62120AEFJ-E2 H-bridge drivers
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Sensors
- INA260 — current sensor for ball count & system load
- BNO055 — IMU for orientation and tilt leveling
- VL53L4CX — ToF distance sensor for range measurement & targeting feedback
- QRD1114 — optical sensors for flywheel speed measurement
- ADS1115 — I²C ADC for additional analog input channels
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Indicators & Controls
- Push button (manual firing trigger)
- WS2812B RGB LEDs for status indication
Version 3 represents the most robust and educationally capable version of SENTRY to date, with major system-level improvements:
- Unified I²C bus architecture with custom breakout board
- Encoder integration on feed belt motor
- VL53L4CX ToF rangefinding for advanced control and targeting
- Relocated QRD1114s for direct flywheel speed measurement
- More accurate ball detection via INA260 current spikes
- ADS1115 I²C ADC for expanded analog sensor support
- Integrated self-test routines for INA260, BNO055, and QRD1114 sensors
- Improved documentation and BOM for replication and classroom use
SENTRY is more than a turret — it is a teaching and research platform. It enables:
- Demonstration of closed-loop feedback control
- Practical labs on PID tuning and system stability
- Exploration of sensor fusion and redundancy
- Robotics coursework involving computer vision, control systems, and mechatronics integration
- A fun, tangible way to connect engineering theory to practice
- Generate and publish full Bill of Materials (BoM)
- Finish development of handheld controller
- Create system wiring/block diagram for documentation
- Develop example student labs (PID tuning, tilt leveling, ball counting)
- Expand Oak-D Lite + Raspberry Pi 4 integration for vision-based targeting
- Continue refining firing logic and feed control with encoder feedback
Contributions and improvements are welcome!
Feel free to fork, submit pull requests, or open issues for discussion.
⚡ This project is actively used in robotics and controls engineering education. Expect frequent updates as new features, documentation, and hardware iterations are released.