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Open nowPosted 145 days ago

Force-aware Policy 算法工程师

x2-robot/91213080 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen nowForce-aware Policy 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.

12.1% 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. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 145 days ago

The posting

1. Force-aware Policy 架构研发 - 负责复杂机器人系统（双臂、灵巧手、高自由度人形）在接触密集任务上的策略研发 - 主导前沿生成式策略的架构设计与系统消融 - 设计多模态信号融合方案，让高频力通道与低频视觉通道在同一 policy 内分工明确；探索异构动作空间（pose / joint / tactile / force）设计方案 2. 多模态感知融合与交互控制 - 利用 6D 力 / 力矩、指尖触觉（GelSight 族）、视觉、语言等多模态输入，建立 Sensorimotor 闭环 - 针对接触密集（contact-rich）场景开发自适应策略，解决多对象操作、对接触状态泛化难题 - 设计并验证“力 / 触觉”两类传感器在不同接触任务上的分工，产出可发表的系统消融结论 3. 真机部署与硬件联调 - 在执行机侧落地软件控制器（目标 ≥ 100 Hz 闭环带宽），消费 policy 输出的 (pose, force) 异质动作 - 深入参与硬件联调，解决传动带来的迟滞、摩擦、抖动等非线性工程问题，保证算法在真机上的鲁棒性 - 搭建推理机 / 执行机分离的低延迟通信管线，保证高频力闭环与低频 policy chunk 推理稳定协同

1. 学历与专业 - 硕士及以上学历，机器人、控制科学、计算机、人工智能等相关专业 2. 核心算法栈 - 模仿学习与生成式策略：精通 BC、Transformer-based Policy（ACT、Decision Transformer）、Diffusion Policy 等前沿架构，理解其数学原理与训练细节 - VLA 与多模态大模型：熟悉 π₀ / OpenVLA / RDT 等 VLA 架构，理解 vision-language backbone 与 action expert 的耦合方式及在接触任务上的局限 - 控制与动力学基础：熟悉现代控制理论（LQR、MPC、WBC、阻抗 / 导纳控制、hybrid force-position control），能讨论为什么软导纳在刚性接触下会震荡 3. 工程落地能力 - 编程：精通 Python / C++，熟练使用 PyTorch，熟悉 ROS / ROS2 通信架构 - 训练栈：有 Hydra + Accelerate 多 GPU + WandB experiment tracking 的实战经验 - 数据管线：能处理多路异步多模态流（RGB 30 Hz + F/T 200 Hz + 触觉 20 Hz）的对齐、下采样与 reduced token 设计 【加分项】 - 真机实战经验：在双臂、灵巧手（Shadow / Inspire 等）或人形机器人上有成功的 IL / VLA 算法部署经验 - 力觉 / 触觉信号处理：6D F/T 重力补偿、external wrench 估计、噪声门限；GelSight 族触觉（Xense、DIGIT、GelSight）的 reduced token 设计或实操 - VLA 训练经验：π₀ / OpenVLA / RDT 或类似架构的后训练、LoRA、action head 替换实战经验 - 遥操作数据管线：搭建 teleoperation 系统并处理大规模人类演示数据（human demo）的经验 - 学术 / 开源影响力：在 RSS、ICRA、CoRL、NeurIPS、IROS 发表过 Robot Learning 相关一作论文，或维护过高 Star 开源项目

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