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Open nowPosted 36 days ago

灵巧手真机评测科研实习生

sii-czxy/campus170 open roles

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Your applicationOpen now灵巧手真机评测科研实习生sii-czxy/campus

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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. 57.8%60 days
This job: posted 36 days ago

The posting

1. 参与灵巧手、机械臂、第一人称视角相机及其他视觉传感器的接入、调试与系统集成，完成设备标定、传感器同步和机器人控制接口开发。 2. 部署视觉—语言—动作模型（VLA）和世界动作模型（WAM）的推理流程，搭建从第一人称视角图像、语言指令和历史观测输入，到动作生成、未来状态预测和机器人执行的完整实验链路。 3. 调试机器人动作坐标转换、执行频率、推理延迟和控制参数，研究真实系统时延约束下利用世界动作模型（WAM）预测结果辅助机器人动作选择与优化的方法。 4. 建立仿真环境与真实机器人系统的批量评测流程，在不同物体、任务场景、视角变化、任务难度和重复实验条件下，评估视觉—语言—动作模型的动作成功率、世界动作模型预测准确性、推理效率和系统稳定性。 5. 对比第一人称视角观测结果与机器人真实执行结果之间的差异，分析模型在视角变化、环境变化以及长步骤任务中的性能表现，定位影响机器人操作效果的关键因素。 6. 整理机器人实验数据、失败案例和评测报告，分析仿真到真机迁移过程中的性能差异，为模型训练、第一人称视角数据构建和任务设计优化提供改进依据。

1. 招募对象：本科生、硕士研究生。 2. 专业背景：机器人、自动化、控制、计算机、电子信息、机械电子等相关专业优先。 3. 具备 Python 或 C++ 编程基础，了解机器人系统、自动控制或计算机系统基本概念，能够参与机器人设备调试和实验开发。 4. 了解机器人坐标变换、运动学、控制基础等相关知识，能够协助定位软硬件联调过程中的问题；具有 ROS/ROS 2、机器人模型部署、实时推理、视频预测或自动化评测经验者优先。 5. 有机器人竞赛、硬件开发、视觉传感器系统、机械臂控制、视觉—语言—动作模型（VLA）部署或机器人系统集成经历者优先；不要求已有正式科研经历或论文发表。 6. 能够阅读英文技术文档和开源项目资料，具备较强的问题分析、故障排查和实验记录能力。 7. 对具身智能、机器人操作、灵巧手控制、视觉感知与机器人智能交互方向具有持续兴趣，能够主动学习相关技术并参与科研任务。 8. 具备较强的团队协作能力，能够稳定参与现场设备调试、实验执行和阶段性研究汇报。 9. 实习安排：线下科研实习；实习周期：3–6个月；每周投入时间：20–30小时。

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