This project involves developing a deep learning model to predict steering angles for an autonomous vehicle. The model is integrated with a Raspberry Pi 4 Model B for real-time operation and control of the vehicle. here
- Deep Learning Model: Predicts steering angles from images captured by a front-mounted camera.
- Real-Time Operation: Deployed on a Raspberry Pi 4 Model B.
- Integration: Connects with hardware components such as a servo motor for steering adjustments.
- Preprocessing: Images are resized and normalized for improved model accuracy.
- Road Segmentation: Utilizes a pretrained model to assist with identifying drivable areas.
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Hardware:
- Raspberry Pi 4 Model B
- Front-mounted camera
- Servo motor
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Software:
- Python
- TensorFlow
- OpenCV
- CARLA simulator (for data collection)
- Clone the Repository:
git clone <repository_url> cd <repository_directory>
- Data Discrepancies: Bridging the gap between simulation and real-world data to improve accuracy.
- Track Design: Ensuring the turning radius in simulations matches the real-world vehicle.
- Signal Noise: Addressing noise in the servo motor signal to reduce instability.
- Enhanced Data Collection: More real-world data for better model performance.
- Track Accuracy: Refining simulation tracks to match real-world dynamics.
- Noise Reduction: Implementing advanced filtering techniques for smoother control.
This project is licensed under the MIT License. See the LICENSE file for details.
- CARLA Simulator
- TensorFlow and Keras
- OpenCV