Merge pull request #6 from yezzfusl/test

README UwU 🥺👉👈

README.md

@@ -1,2 +1,88 @@
 # AeroBrainSTM
 Autonomous STM32H743ZI Drone System
+
+## Hardware Requirements
+
+- STM32H743ZI microcontroller board
+- GPS module (e.g., NEO-6M)
+- LIDAR sensor (e.g., TFMini Plus)
+- OV7670 camera module
+- Telemetry module (e.g., XBee)
+- IMU (Inertial Measurement Unit)
+- Drone frame and motors
+
+## Software Requirements
+
+- STM32CubeIDE (version 1.8.0 or later)
+- ARM GCC Toolchain
+- OpenOCD for flashing
+## Key Features
+
+1. **Flight Control**: Implements PID-based stabilization for roll, pitch, and yaw.
+2. **GPS Navigation**: Utilizes GPS data for waypoint navigation.
+3. **Obstacle Avoidance**: Uses LIDAR data to detect and avoid obstacles.
+4. **Path Planning**: Generates and follows optimal paths between waypoints.
+5. **Telemetry**: Enables real-time data transmission and remote command reception.
+6. **Computer Vision**: Incorporates image processing for scene analysis and decision-making.
+
+## Build Instructions
+
+1. Clone the repository:
+
+`git clone https://github.com/yezzfusl/AeroBrainSTM.git`
+
+`cd AeroBrainSTM`
+
+2. Build the project:
+
+`make`
+
+3. Flash the binary to the STM32H743ZI:
+
+`openocd -f interface/stlink.cfg -f target/stm32h7x.cfg -c "program build/autonomous_drone.elf verify reset exit"`
+
+## Usage
+
+1. Power on the drone system.
+2. Use the telemetry interface to:
+- Add waypoints
+- Start the mission
+- Monitor drone status
+- Abort the mission if necessary
+
+## Technical Details
+
+- **Microcontroller**: STM32H743ZI (Arm Cortex-M7, 400 MHz, 2 MB Flash, 1 MB RAM)
+- **GPS**: UART communication, NMEA sentence parsing
+- **LIDAR**: I2C or UART communication, distance measurement up to 12m
+- **Camera**: OV7670 module, DCMI interface, 640x480 resolution
+- **Telemetry**: UART communication, custom protocol for data exchange
+- **Image Processing**: Basic edge detection using Sobel operator
+- **Path Planning**: A* algorithm for optimal path generation
+- **Obstacle Avoidance**: Reactive avoidance based on LIDAR readings
+
+## Performance Considerations
+
+- The main control loop runs at 100 Hz (10ms cycle time).
+- Image processing is computationally intensive and may impact overall system performance.
+- The system uses DMA for efficient data transfer from peripherals.
+
+## Safety Features
+
+- Geofencing to restrict flight area
+- Failsafe routines for loss of GPS or telemetry signal
+- Low battery voltage detection and auto-return
+
+## Future Improvements
+
+- Implement advanced computer vision algorithms for object detection and tracking
+- Enhance path planning with dynamic obstacle avoidance
+- Add support for multi-drone coordination
+
+## License
+
+This project is licensed under the MIT License - see the LICENSE file for details.
+
+## Contributors
+
+- [@YEZZFUSL]