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Open nowPosted 42 days ago

【实习】slam与三维重建实习生

dx3a2bminsq/93464718 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen now【实习】slam与三维重建实习生dx3a2bminsq/934647 · Shenzhen, Guangdong, Chinese Mainland
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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. dx3a2bminsq/934647 postings stay open a median of 1 days.

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 42 days ago

dx3a2bminsq/934647 median: 1 days open

The posting

一、局部地图构建 1.负责机器人局部环境地图的实时构建与维护,包括占据栅格地图、高程地图、语义地图、ESDF/TSDF 等表示形式; 2.设计地图的更新、衰减与置信度管理机制,保证地图在动态环境下的时效性与一致性; 3.为规划、避障、运动控制等下游模块提供高效、稳定的地图服务接口。 二、多传感器感知融合 1.负责相机、激光雷达、深度相机、IMU、编码器、毫米波雷达等多传感器的数据融合与时空标定(内外参标定、时间同步); 2.开发目标检测、跟踪与多源数据关联算法,提升复杂场景下感知的鲁棒性与精度; 3.处理传感器退化、遮挡、动态干扰等实际工程问题。 三、三维重建与场景理解 1.研发实时/离线三维重建算法(稠密重建、点云拼接、Mesh 生成、纹理重建等); 2.支持基于 3D Gaussian Splatting 在机器人感知与仿真资产生成中的落地; 3.支撑场景语义理解、可通行区域分析等上层应用。

1.计算机、自动化、机器人、电子、测绘等相关专业;能尽快到岗者优先。 2.熟悉感知/建图/SLAM/三维重建相关工作,有机器人或自动驾驶量产/实机项目经验者优先; 3.扎实的数学基础:多视图几何、状态估计、概率论、线性代数、优化理论; 4.精通 C++,熟悉 Python,具备良好的工程能力(ROS/ROS2、Git、CMake、Docker); 5.熟悉至少一种主流技术栈: (1)建图:OctoMap、Voxblox、Grid Map、OpenVDB、Elevation Mapping 等; (2)融合:卡尔曼滤波/因子图优化、多目标跟踪(如 SORT/ByteTrack)、BEV 感知; (3)重建:OpenMVG/OpenMVS、COLMAP、KinectFusion、Open3D、NeRF/3DGS 等; 6.具备较强的分析与解决问题能力,能从实机现象定位到算法或数据问题并闭环解决。

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