Summary of Automated Parking Planning with Vision-based Bev Approach, by Yuxuan Zhao
Automated Parking Planning with Vision-Based BEV Approach
by Yuxuan Zhao
First submitted to arxiv on: 24 May 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Robotics (cs.RO)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed automated valet parking algorithm improves the computational speed and real-time capabilities of planning and optimization for safe and efficient parking. The A* algorithm is integrated with vehicle kinematic models, heuristic function optimization, bidirectional search, and Bezier curve optimization to generate a final parking trajectory. This approach reduces computation time and improves performance in comfort metrics compared to traditional algorithms. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The new automated valet parking system helps self-driving cars park safely and efficiently. It uses a special algorithm called A* that considers the car’s movement and tries different paths to find the best one. The algorithm also ensures the path is safe and doesn’t risk collisions with other objects. This system makes autonomous driving more practical by reducing the time it takes to park. |
Keywords
» Artificial intelligence » Optimization
