小鹏汽车建图融合算法高级/资深工程师
社招全职通用智能板块地点:广州状态:招聘
工作描述
任职要求 1、计算机、自动化、机器人、电子信息、测绘等相关专业,本科及以上学历;具备扎实的数学、计算机视觉、多视几何、状态估计及非线性优化基础; 2、熟悉 Visual/LiDAR SLAM、VIO、SFM、Pose Estimation、Bundle Adjustment、Pose Graph Optimization 等相关技术,具备实际算法研发经验; 3、熟悉 Camera、LiDAR、IMU、GNSS 等多传感器数据处理及融合方法,理解标定、时间同步、坐标系转换、地图配准与对齐等关键问题; 具备矢量地图构建、地图融合、增量建图、地图变化检测或地图更新相关经验,熟悉车道线、道路边界、拓扑关系等地图要素的数据关联与优化; 4、理解道路级/车道级路网构建、拓扑关系及导航信息生成方法,对地图与规划、导航之间的数据链路有较完整理解; 5、具备良好的 C/C++、Python 开发能力,熟悉 Eigen、Ceres、OpenCV、PCL、GTSAM/g2o 等常用工具或库,具备良好的工程实现和问题定位能力。 加分项 1、有自动驾驶、高精地图、众包建图、在线建图或量产项目落地经验; 2、有多车/多…
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包括英文材料
学历+
OpenCV+
https://learnopencv.com/getting-started-with-opencv/
At LearnOpenCV we are on a mission to educate the global workforce in computer vision and AI.
https://opencv.org/university/free-opencv-course/
This free OpenCV course will teach you how to manipulate images and videos, and detect objects and faces, among other exciting topics in just about 3 hours.
SLAM+
https://docs.mrpt.org/reference/latest/tutorial-slam-for-beginners-the-basics.html
[英文] SLAM for Dummies
https://dspace.mit.edu/bitstream/handle/1721.1/119149/16-412j-spring-2005/contents/projects/1aslam_blas_repo.pdf
A Tutorial Approach to Simultaneous Localization and Mapping
https://ouster.com/insights/blog/introduction-to-slam-simultaneous-localization-and-mapping
SLAM is an essential piece in robotics that helps robots to estimate their pose – the position and orientation – on the map while creating the map of the environment to carry out autonomous activities.
[英文] What Is SLAM?
https://www.mathworks.com/discovery/slam.html
How it works, types of SLAM algorithms, and getting started
算法+
https://roadmap.sh/datastructures-and-algorithms
Step by step guide to learn Data Structures and Algorithms in 2025
https://www.hellointerview.com/learn/code
A visual guide to the most important patterns and approaches for the coding interview.
https://www.w3schools.com/dsa/
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