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Open nowPosted 107 days ago

强化学习算法（运控）

zcnma1sv5kma/index41 open roles

Where
Suzhou, Jiangsu, Chinese Mainland
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Your applicationOpen now强化学习算法（运控）zcnma1sv5kma/index · Suzhou, Jiangsu, Chinese Mainland

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Early applications get read.

12.3% 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. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: posted 107 days ago

The posting

1.负责机器人全身运动控制算法研发,包括步态生成、关节空间/任务务空间控制、浮动基动力学控制、接触约束处理与实时控制策略优化。 2.建立遥操作到不同机器人本体的运动映射方法,解决自由度差异、运动范围约束、关节耦合与运动自然性问题,支持跨平台快速迁移。 3.设计并实现复杂优化控制方法,包括轨迹优化、MPC、WBC、IK/QP、力位混合控制与接触稳定性优化,支撑动态行走、奔跑及复杂地形运动。 4.探索强化学习、模仿学习与残差控制在全身运动控制中的的应用,提升机器人在行走、奔跑、抗扰恢复及长程运动任务中的稳定性与成功率。 5.与硬件、嵌入式、数据和应用团队协作,完成控制算法在真实机器人平台上的部署、调试、性能评测与持续迭代。

1.机器人、控制、自动化、机械电子、计算机或相关专业背景,熟悉机器人运动学、动力学与控制理论基础。 2.熟悉复杂优化控制方法,有IK、QP、轨迹优化、MPC、WBC、阻抗/导纳控制或接触丰富任务控制经验。 3.熟悉强化学习或模仿学习方法,理解policy learning、reward design,sim-to-real、domain randomization等概念。 4.有双足/四足机器人、人形机器人、移动操作机器人或高自由度机器人控制相关经验。 5.熟悉Python/C++,能使用MuJoCo、Isaac Sim、PyBullet、ROSS/ROS2或其他机器人仿真与控制工具链。 6.具备真实机器人系统调试能力,能定位控制不稳定、延迟、标定误差、传感器噪声和硬件约束带来的问题。 加分项 1.做过双足/四足行走控制、全身运动控制、动态平衡恢复、复杂地形适应或高动态运动相关项目。 2.有动作捕捉、IMU、力/力矩传感器、编码器或激光雷达等机器人感知与交互设备经验。 3.熟悉RLHF、offlineRL、diffusion policy、residual policy、worled model或robot foundation model相关方法。 4.有真实机器人sim-to-real、自动化数据采集、控制策略评测或故障诊断经验。 5.有从论文复现到真实设备部署的完整经历,能在仿真和硬件之间快速闭环。

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