Develop and implement global path planning algorithms for autonomous vehicles, including A* algorithm, Dijkstra algorithm, etc., to ensure that the vehicle can take the optimal path from the starting point to the destination.
Develop and maintain path planning modules and RNDF visualization tools to ensure their stability, performance and scalability
Based on map data and environmental information, path planning algorithms are designed and optimized, taking into account factors such as road topology and traffic rules.
Analyze and solve problems that arise during path planning, including path adjustment and re-planning in dynamic environments.
Work with other team members to integrate global path planning functionality into the autonomous driving system and conduct system-level testing and verification.
Requirements:
Bachelor's degree or above in Computer science, Electrical Engineering, Automation Control or related fields.
Have experience in developing autonomous vehicle or robot path planning algorithms, and be familiar with path search algorithms such as A* algorithm and Dijkstra algorithm.
Proficient in C++, Python and other programming languages, and have good practical experience in software engineering.
Be familiar with Qgis visualization tools, understand topological formats, and have the ability to programmatically load components (plugins) to enhance and expand QGIS functions.
Good teamwork skills, good communication skills and problem-solving skills.
Have the ability to learn independently and quickly adapt to new technologies, and have a strong interest in autonomous driving technology.
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