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Open nowPosted 38 days ago

操作任务规划工程师

wcn7iq2vq1am/86371186 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now操作任务规划工程师wcn7iq2vq1am/863711 · Shanghai, 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. 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. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: posted 38 days ago

wcn7iq2vq1am/863711 median: 1 days open

The posting

1. 负责机器人操作任务中的规划与求解能力建设，基于公司现有技术栈，面向抓取、避障、轨迹生成、物体操作等典型场景，完成运动规划模块的接入、适配、调试与交付。 2. 针对不同任务约束，设计和实现经典规划、优化方法与学习方法相结合的任务求解流水线，并在仿真及真实机器人环境中完成验证、性能优化和失败案例分析。 3. 参与软体物体操作能力探索，面向布料、线缆、柔性包装等对象，研究和实现形变状态估计、抓取点选择与操作轨迹生成等方法，探索物理模型与学习方法相结合的解决方案。 4. 参与机器人操作数据生成流水线建设，包括 MimicGen 等数据生成方法的部署、复现与工程化，完善示教采集、轨迹切分、数据生成、质量验证及失败归因流程，提升新任务数据生产效率。 5. 将规划和任务求解能力接入场景生成、数据生成、策略训练与真实机器人执行链路，持续完善模块接口、评测方法与工程可维护性，推动相关能力平台化和跨团队复用。 6. 与算法、仿真、控制及数据团队协作，针对具体机器人任务快速定位问题、迭代方案并推动落地。

1. 机器人、计算机、自动化、控制、人工智能、机械等相关专业硕士及以上学历，具备较强的机器人算法与工程实现能力。 2. 熟悉常见机器人运动规划方法，包括采样类、优化类等方法，理解碰撞检测、逆运动学、轨迹生成、抓取规划等基础问题；有机械臂操作或移动操作项目经验者优先。 3. 具备一定模仿学习、强化学习或学习型机器人规划经验，能够理解经典规划与学习方法各自的适用场景，并进行组合和工程落地。 4. 对软体物体、形变物体或铰接物体的建模与操作具有一定理解；有布料、线缆、软体仿真、FEM、关键点检测等相关经验者优先。 5. 熟练使用 Python / C++，能够独立在机器人仿真环境中搭建任务、调试算法，并具备较好的代码工程能力和问题定位能力。 6. 具备较强的跨团队协作和执行能力，能够承接任务需求、拆解问题、快速验证方案，并推动能力沉淀与复用。 7. 对机器人操作、任务规划、数据生成及 sim-to-real 等方向有较强兴趣。

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