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Open nowPosted 357 days ago

运控算法工程师（轮式类人机器人）

agirobot/referral514 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now运控算法工程师（轮式类人机器人）agirobot/referral · Shanghai, Chinese Mainland

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  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

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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. agirobot/referral 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 357 days ago

agirobot/referral median: 1 days open

The posting

负责轮式类人机器人运动规划与控制算法的研发，涵盖自主导航、全身运动规划、轨迹优化及数据驱动的运动生成。结合全向移动底盘、高自由度上肢及复杂环境约束，融合经典规划控制与学习方法，提升机器人的自主移动、避障与操作能力。 主要职责 1. 自主导航与运动控制： 研发全向移动底盘的路径规划、局部轨迹优化、动态避障及轨迹跟踪算法，结合环境地图与机器人运动约束，实现复杂场景下安全、平滑的自主导航。 2. 全身运动规划与控制： 面向底盘、腰部、躯干及双臂的协调运动，研究逆运动学、碰撞检测、运动规划、轨迹优化及全身控制等算法，实现满足运动学、动力学及环境约束的机器人运动。 3. 学习增强的运动规划与生成： 研究采样、优化与学习相结合的规划控制方法；探索利用语义地图、VLM/VLA 的场景理解及任务目标生成运动约束、路径或动作序列，并结合模仿学习、强化学习及生成式模型提升运动规划与生成能力。 4. 算法部署与系统优化： 完成相关算法的仿真验证、真机部署、性能优化及系统联调，面向自主导航、移动操作及人机交互等场景推动产品落地。

1. 教育背景： 机器人、自动化、控制工程、计算机或相关专业硕士及以上学历，具备 2 年以上机器人算法开发经验。 2. 专业基础： 具备扎实的机器人学、运动学及控制理论基础，至少深入掌握以下一个方向： - 运动规划与优化： 熟悉搜索、采样、轨迹优化、最优控制或模型预测控制等算法，具有机器人避障规划或全身运动规划经验。 - 机器人导航与控制： 熟悉环境地图表达、全局与局部路径规划、动态避障、轨迹跟踪等算法及其工程实现。 - 学习型运动生成： 熟悉模仿学习、强化学习、运动基元或扩散模型、流匹配等生成式方法，具有机器人运动规划或控制相关经验。 3. 工程能力： 熟练掌握 C++、Python，具备良好的软件工程能力；熟悉 ROS2，具有机器人算法开发、调试与性能优化经验。 4. 算法框架与仿真： 熟悉 Pinocchio、OMPL、Nav2、CasADi、OSQP 等相关工具中的一种或多种；了解 MuJoCo、Isaac Sim、Isaac Lab 等仿真平台，具备算法仿真验证或真机部署经验。 5. 综合能力： 具备独立分析与解决实际机器人问题的能力，能够结合运动约束、实时性及安全性要求完成算法工程化。 加分项 1. 有轮式类人机器人、移动操作机器人或自主移动机器人实际开发经验，或 RoboMaster、ROBOCON 等机器人竞赛经历。 2. 有语义导航、VLM/VLA 驱动的运动规划，或学习与优化结合的机器人规划控制研究经验。 3. 在 ICRA、IROS、RSS、CoRL、Humanoids 等会议或 T-RO、IJRR、RA-L 等期刊发表过相关论文。

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