Responsibilities:
- 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.
