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Open nowPosted 129 days ago

【27届】语义地图算法工程师

x2-robot/91213080 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen now【27届】语义地图算法工程师x2-robot/912130 · Shenzhen, Guangdong, Chinese Mainland

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The clock on this job

Early applications get read.

11.8% 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. 4.4%3 days
  3. 11.8%7 days
  4. 18.5%14 days
  5. 35.5%30 days
  6. 45.1%60 days
This job: posted 129 days ago

The posting

1. 多模态语义理解与特征融合：负责利用开放词汇（Open-Vocabulary）检测/分割模型（如 YOLO-World, Grounding DINO, SAM 等）或 VLM 先验，实时提取家庭环境中的三维物体标签、空间边界及场景属性。 2. 实现语义特征与传统 SLAM 几何数据（RGB-D、LiDAR、IMU）的鲁棒时空对齐与数据关联。 3. 分层拓扑地图架构设计 (Layered Mapping)： 设计并实现多层联动地图架构，包括但不限于：底层几何层（栅格地图/TSDF）、中间物体/属性层（3D Bounding Box / 语义稠密网格）、高层拓扑层（房间连通图/语义关系图）。 4.基于维诺图及图论的空间表征 (Generalized Voronoi Diagram)：负责研发基于广义维诺图（GVD / Voronoi Diagram）或骨架提取算法的空间拓扑化表征技术。 利用维诺图将复杂的 2D/3D 家庭自由空间压缩为一维拓扑中轴线网络，提取关键拓扑节点（如房门、狭窄通道），用于实现低功耗、高效率的路径规划与语义划分。 5. 动态地图更新与记忆反思机制 (Map Maintenance)： 研发针对家庭场景的长周期、动态地图更新算法，有效处理家具移动、房门开关、人员走动等引起的地图环境变更。 6. 设计增量式更新（Incremental Update）与概率维护机制，确保地图信息在数天或数月运行后的时空一致性与语义鲁棒性。 7. 端侧部署与跨团队打通：负责将算法移植、量化并优化部署在边缘端计算平台，配合 VLN（视觉语言导航）算法团队，实现高效的语义地图查询、拓扑定位与大规模语义数据存储。

1. 毕业时间介于2026年9月至2027年8月的国内外高校的本科生、硕士生、博士生，计算机、自动化、机器人、测绘遥感等相关专业优先。 2. 精通 Python 和 C++，具备优秀的软件架构设计能力和高效的数据结构与算法基础。 3. 深入理解经典 2D/3D SLAM 与状态估计理论（如激光激光 SLAM、视觉 SLAM 或三维重建）。 4. 熟练掌握图论与计算几何基础，有维诺图（Voronoi Diagram）、Delaunay 三角剖分、拓扑骨架提取或图搜索算法（$A^$, Dijkstra, HPA）的实际开发经验。 5. 熟悉深度学习在三维视觉中的应用（如三维物体检测、语义分割、开放词汇识别）。 6. 熟练掌握 Linux 环境，精通 ROS/ROS2 机器人操作系统，熟练使用 OpenCV、PCL（Point Cloud Library）、g2o/Ceres 或图形数据库。

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