https://github.com/orcos-nom/aiodr
artificial intelligence object detection rover
https://github.com/orcos-nom/aiodr
computer-vision-opencv deep-learning esp32 esp32-cam machine-learning object-detection python3 real-time-detection robotics tensorflow yolov8
Last synced: 2 months ago
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artificial intelligence object detection rover
- Host: GitHub
- URL: https://github.com/orcos-nom/aiodr
- Owner: Orcos-nom
- Created: 2024-11-24T04:11:08.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-26T07:02:04.000Z (over 1 year ago)
- Last Synced: 2025-04-03T06:48:32.032Z (about 1 year ago)
- Topics: computer-vision-opencv, deep-learning, esp32, esp32-cam, machine-learning, object-detection, python3, real-time-detection, robotics, tensorflow, yolov8
- Language: C
- Homepage:
- Size: 80.1 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# 🤖 AIODR - Artificial Intelligence Object Detection Rover
[](https://www.espressif.com/en/products/socs/esp32)
[](https://www.python.org/)
[](https://docs.ultralytics.com/)
[](https://opensource.org/licenses/MIT)
**AIODR** is an advanced Bluetooth-controlled rover that integrates robotics with real-time AI object detection. By combining the **ESP32** ecosystem with **YOLOv8**, this project serves as a powerful bridge between IoT hardware and computer vision.
---
## 📸 Media & Demos
| **Physical Rover** | **Cad design** |
| :---: | :---: |
| 
| 
|
| *Assembled ESP32 Rover* | *Fusion 360 CAD design* |
---
## **Features**
- **📲 Bluetooth Control**
Operate the rover effortlessly through a custom mobile app, providing real-time directional control and feedback.
- **📸 Object Detection**
Harnesses the power of YOLOv8 to detect and classify objects with high accuracy and efficiency.
- **🌄 Camera Integration**
Equipped with the ESP32-CAM module to capture live video streams and provide continuous image processing.
- **🧠 AI-Powered Processing**
Leverages machine learning frameworks like TensorFlow and YOLOv8 for precise object identification and tracking.
- **💻 Python Backend**
Robust detection algorithms built using Python 3, utilizing OpenCV and NumPy for image preprocessing and analysis.
---
## **Technologies Used**
| Component | Description |
|-------------------|-------------------------------------------------------------|
| **ESP32** | Handles Bluetooth communication and controls motor movement |
| **ESP32-CAM** | Captures and streams video for AI-based processing |
| **Python 3** | Core programming language for detection and control logic |
| **OpenCV & NumPy** | Provides image processing and numerical analysis tools |
| **TensorFlow** | AI framework for object detection and classification |
| **YOLOv8** | Real-time object detection algorithm |
---
## **How It Works**
1. The ESP32 microcontroller establishes a Bluetooth connection with the mobile app.
2. Commands sent via the app control the movement of the rover (forward, backward, left, right).
3. The ESP32-CAM captures live video, streaming it to a Python processing unit.
4. Using OpenCV and NumPy, the video frames are processed and fed into the YOLOv8 model.
5. Detected objects are labeled and visualized in real-time on the mobile app or display.
---
## **Applications**
AIODR has a wide range of practical applications, including:
- 📚 **Educational Robotics & AI Learning**
Perfect for students and enthusiasts exploring robotics and artificial intelligence.
- 🛡️ **Surveillance & Monitoring Systems**
Can be deployed for home security and remote monitoring.
- 🚒 **Autonomous Navigation**
Potential to develop self-driving algorithms for exploration and obstacle avoidance.
- 🌱 **Agriculture & Environment Monitoring**
Useful for monitoring crops, livestock, and environmental conditions.
- 🏛️ **Industrial Applications**
Can assist in warehouse automation and quality inspection tasks.
---
## **Getting Started**
### **Hardware Requirements:**
- ESP32 Development Board
- ESP32-CAM Module
- MG995 Servo Motor
- 100 RPM DC Motors (x2)
- L298N Motor Driver
- Li-ion Battery Pack
- 3D-printed chassis and laser-cut acrylic parts
### **Software Requirements:**
Make sure to install the following dependencies before running the project:
```bash
pip install opencv-python numpy tensorflow ultralytics
```
### **Installation Steps:**
1. Clone this repository:
```bash
git clone https://github.com/Orcos-nom/AIODR.git
cd AIODR
```
2. Flash the ESP32 with the provided firmware using the Arduino IDE.
3. Run the Python detection script on your PC:
```bash
python detection.py
```
4. Connect the mobile app via Bluetooth and control the rover.
---
## **Future Improvements**
We have several exciting plans to enhance AIODR, such as:
- 🧠 Implementing cloud connectivity for remote monitoring.
- 🌐 Enhancing object detection with custom-trained models.
- 🛠️ Adding autonomous path planning with obstacle avoidance.
- 🌟 Improving energy efficiency for prolonged operation.
---
## **Contributing**
We welcome contributions from the community! If you'd like to contribute to AIODR, feel free to submit pull requests or open issues to suggest enhancements and bug fixes.
---
## **License**
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
---
## **Acknowledgments**
Special thanks to all contributors and the open-source community for their invaluable resources and support. Let's keep innovating! 🚀
---
**Follow the project and stay updated on future developments!**
---