Problem Statement & Solution
Urban mobility poses unique challenges in ensuring safe navigation for autonomous vehicles. The complexity of city environments requires advanced vision-based systems that can interpret surroundings and make real-time decisions for safe navigation.
Our team developed an advanced computer vision-based system using the TurtleBot Burger robot to navigate safely through urban environments. The system incorporated AI-driven image processing, object detection, and path optimization to ensure precise navigation in real-time.
Key Features
- Computer Vision: Implemented object detection algorithms to recognize obstacles and pedestrians.
- Safe Path Planning: Optimized route navigation based on real-time data from sensors.
- Autonomous Navigation: Ensured the robot could operate autonomously without human intervention.
- Sensor Fusion: Integrated multiple sensors for enhanced accuracy and reliability in decision-making.
Benefits
- Safe Navigation: Revolutionized urban transportation by enabling autonomous vehicles to navigate safely through busy city environments.
- Urban Mobility: Paved the way for more effective and sustainable urban mobility solutions.
- Real-World Impact: Demonstrated the potential for computer vision and AI in enhancing the safety and efficiency of autonomous vehicles.
Skills
- Computer Vision
- ROS1 Noetic Framework
- Sensor Integration
- Sign detection Algorithms
- Lane detection
- Auto Parking
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