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Open nowPosted 136 days ago

具身智能触觉算法工程师（强化微调与力控方向）

x2-robot/index203 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen now具身智能触觉算法工程师（强化微调与力控方向）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. 18.5%14 days
  5. 35.5%30 days
  6. 45.1%60 days
This job: posted 136 days ago

x2-robot/index median: 1 days open

The posting

岗位背景 机器人在真实环境中完成接触式操作时，需要具备对接触状态、受力变化和执行反馈的持续感知能力。触觉与力觉反馈能够帮助策略更好地理解交互过程，并在操作过程中提升稳定性与安全性。 本岗位主要面向具身智能中的触觉策略学习方向，关注触觉/力觉反馈在真机强化微调、人工接管纠偏、策略优化和力控协同中的应用，提升模型在接触交互过程中的适应能力与执行质量。 岗位职责 1. 负责触觉/力觉反馈驱动的真机强化微调、模仿学习或策略优化算法研发。 2. 设计机器人策略微调中的观测、动作、奖励、约束和数据回流机制。 3. 研究人工接管、在线纠偏和失败恢复数据在策略更新中的使用方式。 4. 研究学习策略与力控、阻抗控制等控制接口的协同方式。 5. 分析机器人执行过程中的失败案例，持续优化策略稳定性、鲁棒性和安全性。 6. 与控制、感知、硬件和平台工程同事协作，完成算法集成与实验验证。

任职要求 1. 计算机、机器人、自动化、控制、机械电子、人工智能等相关专业本科及以上学历。 2. 熟悉强化学习、强化微调、模仿学习或机器人学习中的一种或多种方法。 3. 了解机器人运动学、动力学以及控制基础，理解末端位姿、速度控制、力控、阻抗控制等基本概念。 4. 熟悉 Python/C++，具备良好的算法实现、实验调试和工程落地能力。 5. 了解真实机器人实验流程、数据采集流程或机器人控制接口。 6. 具备较强的问题分析能力，能够基于日志、曲线和实验现象定位算法或控制问题。 加分项 1. 有真机强化学习、在线微调、人工接管、DAgger、残差策略或安全强化学习相关经验。 2. 有触觉传感器、六维力传感器、灵巧手、机械臂相关经验。 3. 有真实机器人在线数据采集、策略部署、实验调试或失败 case 复盘经验。 4. 熟悉 VLA、action model、策略蒸馏、策略正则化或基于基础模型的策略微调方法。 5. 熟悉 ROS/ROS2、机器人 SDK、策略部署接口或阻抗/导纳控制基础。

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