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Open nowPosted 35 days ago

感知算法工程师（激光雷达传统算法）

n8o893zm8h/index24 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now感知算法工程师（激光雷达传统算法）n8o893zm8h/index · Shanghai, Chinese Mainland

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Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 57.8%60 days
This job: posted 35 days ago

The posting

1、激光点云分割算法研发，负责灰尘、地面、档墙、车辆等的分割识别和过滤。负责土堆等的识别和尺寸测量。 2、几何处理与特征工程，研发先进的点云预处理算法，包括：地面滤波、点云聚类、离群点去除、点云配准与畸变校正。探索几何深度学习方法，将点云的几何特征（法向量、曲率、局部邻域）融入神经网络，提升分割的几何保真度。 3、多模态融合与矢量化，结合摄像头图像信息，解决点云稀疏区域的分割模糊问题，实现跨模态对齐与融合。参与将分割结果转换为矢量化地图要素（高精地图更新）或障碍物边界框的后处理工作。 4、负责模型在车载嵌入式平台的部署与加速，保证感知链路的低延迟。建立模型Bad Case分析与数据回流机制，持续提升分割模型在Corner Case上的表现。

1、硕士及以上学历，计算机视觉、自动化、机器人学、测绘遥感等相关专业。 2、硬性技能：极扎实的C++/Python编程能力，熟悉PCL（点云库）和Open3D，熟练使用PyTorch及MMDetection3D/OpenPCDet框架。 3、算法理解：熟悉和理解常用的点云分割网络，熟悉稀疏卷积与体素化方法的优缺点。 几何感知：对三维空间几何变换有较深刻理解，熟悉RANSAC、ICP等经典几何算法，并能将其与现代深度学习模型结合解决实际问题。 4、熟悉激光雷达与相机的联合标定与投影融合，有BEV空间下多模态融合感知经验。有模型量化（TensorRT/OpenVINO）及嵌入式平台（Orin， 地平线J6， TDA4）部署经验。

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