This project aims at integrating robust algorithms for object pose estimation and tracking as vision guidance for industrial robotic manipulators. Such vision-based control will be applied to industrial tasks such as bin picking and object pick-and-place from shelves. The main goal of the project is to achieve robust vision-based robot control using inexpensive sensors, in comparison to standard expensive industrial ones. The project includes both testing of the perception part, as well as integration with the path planning and grasping algorithms.
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| Title: | Vision-based Robotic Pick and Place (with KUKA Roboter GmbH?) |
| Abstract: | This project aims at integrating robust algorithms for object pose estimation and tracking as vision guidance for industrial robotic manipulators. Such vision-based control will be applied to industrial tasks such as bin picking and object pick-and-place from shelves. The main goal of the project is to achieve robust vision-based robot control using inexpensive sensors, in comparison to standard expensive industrial ones. The project includes both testing of the perception part, as well as integration with the path planning and grasping algorithms. The project is made in collaboration with KUKA Roboter GmbH?, one of the leader companies in the field of industrial robots. The student will be often working directly with KUKA Comporate Research, located in Augsburg (around 35 minutes by train from Munich HBF). The student will receive financial support from KUKA (in the form of a monthly stipend) for the duration of the Master Thesis. |
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| Director: | Prof. Nassir Navab |
| Supervisor: | DavidTan, Salvatore Virga, Federico Tombari |
| Type: | Master Thesis |
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| Status: | finished |
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