Robotics Perception & Autonomy Intern

Relativity Space

Long Beach (CA)

On-site

USD 25,000 - 52,000

Full time

4 days ago
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Job summary

Relativity Space in Long Beach, CA is seeking a student to join the Additive Technology team as a robotics perception intern. You will develop and test perception pipelines for robotic arms and mobile robots, integrating LiDAR, stereo/depth cameras, and 3D sensors.

You will work with ROS2, Python, and C++, contribute to localization, mapping, and cooperative autonomy, and help prototype sensor fusion and motion planning for production systems.

Qualifications

  • Pursuing an undergraduate degree in a technical field (CS, robotics, electrical or mechanical engineering).
  • Proficient in Python and/or C++ with experience in robotics or perception applications.
  • Familiar with ROS2 or other robotics middleware.
  • Strong problem-solving skills and interest in cooperative robotics and autonomy.

Responsibilities

  • Develop and test perception pipelines integrating LiDAR, stereo/depth cameras, and 3D sensors for robotic arms and mobile robots.
  • Contribute to localization, mapping, and cooperative autonomy algorithms for multi-robot teams.
  • Prototype and evaluate sensor fusion approaches combining vision, thermal, and laser data.
  • Support toolpath generation and motion planning for robotic welding, grinding, and gouging tasks and mobile robots.
  • Collaborate with robotics engineers to integrate perception with real-world production systems.

Skills

Python
C++
Robotics
ROS2
Problem-solving

Education

Undergraduate degree in CS/Robotics/EE/ME

Job description

Relativity Space in Long Beach, CA is seeking a student to join the Additive Technology team as a robotics perception intern. You will develop and test perception pipelines for robotic arms and mobile robots, integrating LiDAR, stereo/depth cameras, and 3D sensors.

You will work with ROS2, Python, and C++, contribute to localization, mapping, and cooperative autonomy, and help prototype sensor fusion and motion planning for production systems.

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