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Open nowPosted 36 days ago

仿真数据与机器人学习研究工程师

wcn7iq2vq1am/86371186 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now仿真数据与机器人学习研究工程师wcn7iq2vq1am/863711 · Shanghai, Chinese Mainland

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The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market. wcn7iq2vq1am/863711 postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 36 days ago

wcn7iq2vq1am/863711 median: 1 days open

The posting

1. 负责大规模机器人操作仿真与数据生成系统的研发，覆盖刚体、软体、复杂避障、多指手等具有挑战性的操作技能与任务，持续扩展场景规模、任务多样性和数据分布覆盖，支撑机器人模型的大规模训练与强泛化。 2. 设计和迭代大规模场景与数据生成算法，包括场景采样、机器人初始状态与物体位姿生成、任务约束、可解性验证、corner case 挖掘与自动化测试等。 3. 基于 SAPIEN 等平台构建和验证机器人操作环境，覆盖任务定义、接触与碰撞、动力学、抓取、运动约束以及复杂物理交互。 4. 搭建场景生成、技能训练、RL / motion planning、数据生产与闭环 evaluation 的完整 pipeline，并根据模型表现持续发现失败模式、生成新的训练分布和高价值数据。 5. 负责机器人、物体及 3D 资产的系统化标注与数据体系建设，覆盖 geometry、collision、joint、material、physical properties、grasp pose 等等关键属性，支撑大规模场景生成与数据生产。 6. 参与各类机器人操作技能的 sim2real 对齐研究与实现。

1. 机器人、计算机、自动化、人工智能、图形学等相关方向硕士及以上学历，具备较强的机器人研究、算法设计与工程实现能力。 2. 熟悉至少一种主流机器人仿真平台，如 ManiSkill、SAPIEN、Isaac、MuJoCo，对机器人仿真、任务构建和数据生成有较深入的实践与理解。 3. 对机器人操作中的运动学、动力学、碰撞接触、抓取、任务约束等问题有深入理解，能够对复杂操作问题进行系统分析，并独立设计、验证和迭代解决方案。 4. 具备以下一项或多项深入经验：大规模仿真场景与数据生成、大规模 3D 资产处理与标注、强化学习、sim2real、motion planning、task and motion planning (TAMP)、机器人操作学习。 5. 对如何通过更大规模、更高 diversity、更高质量的数据推动机器人模型泛化有深入兴趣，能够结合模型表现与 failure case，系统分析数据和任务分布中的瓶颈，并持续迭代场景生成算法、训练方法与数据生成系统。

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