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Autonomous Systems
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Self-Driving Car Software Pipeline
A full-stack autonomous driving system integrating computer vision, sensor fusion, and control algorithms for navigating complex environments safely.
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Overview
Developed a comprehensive autonomous driving pipeline focusing on perception, planning, and control. The system utilizes deep convolutional neural networks for lane detection, dynamic object tracking, and traffic sign recognition. It integrates sensor fusion techniques to process multi-modal data in real-time. Extensively trained and validated using MetaDrive simulation to ensure robust performance before hardware deployment.
Key Features
- Real-time lane and dynamic object detection
- Sensor fusion for robust environmental mapping
- Reinforcement learning-based path planning
- High-fidelity simulation validation