We are looking for a Robotics & Computer Vision Intern to build a vision-guided pick-and-place system for a robotic arm. The goal is to let the robot recognize parts on a work cell, decide how to grasp them, and place them accurately, with minimal manual programming.
The project involves building a solution capable of:
- Detecting and identifying the parts used in the cell with a trained object detector.
- Estimating grasp poses directly from camera images.
- Calibrating the camera with the robot arm (hand-eye calibration) for precise positioning.
- Planning collision-free arm motions to pick and place each part.
- Measuring success rate, speed and accuracy in simulation and on the real cell.
Technical Skills
- Experience with Python or C++.
- Computer vision skills with OpenCV.
- Deep learning basics for object detection (PyTorch, YOLO).
- Understanding of robot kinematics and coordinate frames.
