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Robotics Manuplation Intern

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Onsite

Robotics Manuplation Intern

Spritle Software

Robotics Manuplation Intern

Skills

NodePythonAILinux

2 months ago

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Important information


Contract type:

Internship

Location:

Chennai, Tamil Nadu, India

Work mode:

Onsite

Published on:

1 September 2026

What they need


What You'll Work On

  • Develop and test applications for 6-DoF/7-DoF robotic manipulators such as Flexiv, Universal Robots, LeRobot, or equivalent platforms.
  • Work with joint space, Cartesian space, end-effector poses, coordinate frames, and transformations.
  • Implement and test Forward Kinematics (FK) and Inverse Kinematics (IK).
  • Develop motion and trajectory execution workflows.
  • Work with ROS2 nodes, topics, publishers, subscribers, services, TF/TF2, and robot interfaces.
  • Use MoveIt2 or equivalent frameworks for motion planning and collision checking.
  • Integrate robotic manipulators with cameras and perception systems.
  • Perform robot, camera-to-robot, and hand-eye calibration.
  • Develop pick-and-place, manipulation, and automation experiments on physical robots.
  • Test robotic applications in simulation and transfer validated workflows to physical robots.

Must Have

  • Bachelor's/Master's degree or final-year student in Robotics, Mechatronics, Mechanical Engineering, Electronics, Computer Science, or related field.
  • Strong understanding of robotics fundamentals.
  • Understanding of 6-DoF robotic arms and basic manipulator concepts.
  • Good understanding of 3D Cartesian space, coordinate frames, and transformations.
  • Understanding of Forward and Inverse Kinematics concepts.
  • Programming experience in Python; C++ exposure is an advantage.
  • Familiarity with Linux/Ubuntu and Git.

Good to Have

  • ROS2 and TF/TF2.
  • MoveIt2, OMPL, or other motion-planning frameworks.
  • Flexiv, Universal Robots, LeRobot, or similar robotic arms.
  • Robotics simulators such as Gazebo, Isaac Sim, or MuJoCo.
  • Jacobians, singularities, trajectory generation, collision detection, and avoidance.
  • Sim-to-real workflows.
  • Robotic grippers/end-effectors.
  • Vision-guided manipulation, 3D perception, VLM/VLAM, or AI-based robotic manipulation.

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