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Open nowPosted 56 days ago

【27届校招】机器人运动算法工程师

flexivrobotics/97193226 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now【27届校招】机器人运动算法工程师flexivrobotics/971932 · Shanghai, 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.

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 56 days ago

The posting

1. 参与机械臂运动规划算法的设计、开发、仿真验证与真机调试，支持机器人产品在仓储、药房等实际业务场景中的落地应用。 2. 参与多自由度机械臂运动规划相关技术研发，包括路径规划、碰撞检测与避障、轨迹优化、运动平滑、动作生成等方向。 3. 参与机器人操作（Manipulation）能力建设，包括运动规划、抓取策略、Learning-based Policy 与控制算法融合，提升机器人自主操作能力。 4. 基于 C++/Python 参与机器人算法模块开发，包括算法实现、接口设计、仿真验证、通信组件及工程化落地。 5. 与感知、控制、系统软件及现场部署团队协作，参与算法性能优化、系统稳定性提升及问题定位分析。 6. 跟踪机器人操作、运动规划、智能控制等前沿技术，并参与相关算法的验证与应用探索。

1. 扎实掌握机器人运动学、动力学、运动规划及碰撞检测理论，熟悉主流运动规划框架（如 OMPL、Curobo），熟练掌握基于采样或优化的规划算法（RRT、PRM、TrajOpt、CHOMP）。 2. 具备机器人仿真、算法验证或智能操作相关项目经验，了解 PyBullet、MuJoCo、Isaac Sim/Gym、Gazebo 等仿真平台，或接触过 Imitation Learning、Reinforcement Learning、Diffusion Policy、VLA/VLM、Learning-based Manipulation 等前沿方向。 3. 熟悉 Linux 开发环境，具备良好的 C++、Python 开发能力，了解 Bash 脚本及网络通信机制。 4. 熟悉软件工程开发流程，包括软件架构设计、接口设计、版本管理、单元测试及持续集成。

加分项 1. 有机械臂真机调试、手眼标定、轨迹调参、抓取策略优化或 Sim-to-Real 经验。 2. 熟悉 ROS2、MoveIt2、行为树、机器人中间件、通信机制或多模块系统集成。 3. 了解轨迹优化、MPC、非线性优化、约束优化，使用过 CasADi、IPOPT、Drake、Crocoddyl 等工具。 4. 了解力控、阻抗控制、导纳控制、柔顺控制、触觉传感或接触丰富场景下的操作控制，并具备真机调试经验。 5. 有 Diffusion Policy、ACT、RDT、VLA/VLM、模仿学习、强化学习等机器人学习方向项目经验。 6. 熟悉 Isaac Sim、NVIDIA Omniverse、合成数据生成、域随机化、GPU 并行仿真或 Sim-to-Real 流程。 7. 有机器人竞赛、企业实习、开源项目、论文发表或复杂机器人系统项目经历。

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