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Open nowPosted 219 days ago

运动控制算法实习生（强化学习方向）

xiaopeng/campus629 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen now运动控制算法实习生（强化学习方向）xiaopeng/campus · Shenzhen, Guangdong, Chinese Mainland

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The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market. xiaopeng/campus postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 219 days ago

xiaopeng/campus median: 1 days open

The posting

【关于我们】 小鹏机器人中心致力于研发先进的人形机器人技术，覆盖机器人行走、灵巧操作、智能导航，以及在大语言模型支持下的人机交互等方向。我们的软硬件研发团队分布于深圳、上海、广州、北京及北美，汇聚跨学科的一流人才。加入我们，你将参与把人工智能真正落地到物理世界的核心工作，与控制、感知、规划、硬件等多领域工程师紧密协作，攻克前沿科研与工程难题，并推动人形机器人关键能力的持续演进。

【工作职责】 1、参与机器人的强化学习训练，优化机器人运动规划与控制策略，与传统控制方法形成互补，提升整体运动性能； 2、参与机器人数据重映射（retargeting / remapping）与位置/姿态跟踪算法的开发与优化； 3、将先进运动控制与机器学习方法应用于我们的自研人形机器人，推动算法从离线验证到真机闭环； 4、研究和复现前沿强化学习算法，探索相关领域学术和工程问题。

【岗位要求】 1、本科及以上在读，数学、计算机、人工智能、自动化、机器人等相关专业优先； 2、至少 1 年强化学习相关项目或研究经验，熟悉足式机器人运动学和动力学； 3、熟练使用基于 Pytorch 的深度学习框架，掌握 PPO、DQN、SAC 等主流强化学习算法，以及 MuJoCo、Isaac Gym/Sim 等主流仿真工具； 4、热爱机器人行业，有相关期刊或会议论文发表经历，或实际强化学习项目落地经验者优先。

【你将获得】 1、深度参与最前沿的具身智能算法研发，专注于双足机器人运动规划与控制，以及从仿真到实机的迁移； 2、行业内资深专家的指导，对于优秀成果，我们将全力支持发表学术论文或申请专利； 3、完备的实验室支持，包括充足的计算资源、稳定的机器人平台和强大的软硬件团队； 4、明确的成长路径：实习生是公司的重要储备人才，对于即将毕业的优秀实习生，我们优先考虑其全职工作申请。

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