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Open nowPosted 179 days ago

具身操作算法工程师（快慢系统融合）

x2-robot/index203 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen now具身操作算法工程师（快慢系统融合）x2-robot/index · 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. x2-robot/index postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 179 days ago

x2-robot/index median: 1 days open

The posting

1. 负责面向家居、养老等高动态人机交互场景（如抱扶、护理、协作操作）的 System 1 / System 0 分层操作策略研发，构建低频语义规划（1–10 Hz）与高频行为生成（50–100 Hz）协同的统一框架，实现长短时序解耦与稳定闭环控制。 2. 设计并实现 System 1 层的操作语义建模能力，包括轨迹、接触模式与接触力等关键表示，并兼顾任务指令理解、视觉避障与多目标约束下的规划能力。 3. 研发 System 0 层高频控制策略，在关节空间生成稳定、连续且可控的操作行为，实现刚度调节、接触稳定与局部避障能力，并解决高频执行中的延迟、抖动与不连续问题。 4. 应用并拓展行为克隆、强化学习（RL-first paradigm）、生成式策略（Diffusion / Flow Matching）及元学习等方法，构建具备闭环执行、异常恢复与实时适应能力的操作策略。 5. 构建融合视觉、本体感知、力/触觉与语言的多模态具身模型（VLA / WAM），进行多模态信息感知、长-短时序任务目标规划、行为语义规划、运动轨迹生成等任务，并设计适配不同时间尺度的模型架构，实现从语义规划到动作生成的统一建模。 6. 推动算法在真实机器人系统中的部署与优化，参与硬件联调，定位并解决抖动、迟滞、接触不稳定等工程问题，构建推理机与执行机分离的低延迟系统架构，保证高频执行与低频推理的稳定协同。

1. 硕士及以上学历，机器人、控制、计算机、人工智能等相关专业，具备扎实的数学基础与系统建模能力。 2. 熟悉机器人学习方法，包括行为克隆（BC）、强化学习（PPO / SAC 等）或生成式策略（Diffusion Policy、Flow Matching 等），理解 action chunk、轨迹生成与时序建模机制。 3. 熟悉具身多模态建模或大模型架构，如 VLA、WAM 或 Transformer-based policy，理解视觉-动作对齐、长短时序建模与 latent action 表达。 4. 掌握机器人控制基础，包括关节控制、笛卡尔空间控制、阻抗/导纳控制及接触建模，能够分析高频控制稳定性及延迟对系统的影响。 5. 具备较强工程能力，熟练使用 Python（PyTorch）进行模型开发，具备 ROS / ROS2 或机器人系统开发经验，能够处理多模态、多频率数据管线。 6. 具备系统级问题分析能力，能够定位并解决真实系统中的抖动、延迟、轨迹不连续及 sim-to-real gap 等问题，并独立设计实验进行验证与优化。

【加分项】 1. 具备高频控制或 System 0 相关经验，如 100 Hz 以上控制策略设计、learned controller、action 插值或重建等。 2. 有接触丰富（contact-rich）任务经验，如擦拭、装配、人机交互等，熟悉接触模式建模与力控制方法。 3. 有 DP / VLA / WAM / 多模态大模型训练或微调经验，包括多模态 token 设计或 action head 建模。 4. 有真实机器人系统部署经验，熟悉推理延迟优化、异步执行架构或分层控制系统设计。 5. 在具身智能或机器人学习领域（如ICRA, IROS, RSS, TRO, IJRR，RAL）有论文发表或高质量开源项目经验。

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