Brief description:
Background:
The automation of industrial processes is getting more and more important in the field of meat processing too, however this poses serious technical challenges in several respects as well. Due to food safety regulations and the natural biological diversity of plants and animals, the reliable automation of these processes requires the development of new kinds of “smart” devices (knives, grippers, etc.) that ensure the safe and reliable operation.
Task:
This topic deals with the development of the software of a “smart meat gripper”, reliable slip detection has to be achieved based on opticalflow calculation of the video-feed of the endoscope camera placed inside the gripper. Software development should be optimized for the Raspberry Pi compute module built into the gripper.
Programming languages, environments: ROS, Python, OpenCV
Task details:
- Getting to know the task-specific challenges of meat industry automation
- Mapping opticalflow-based methods
- Planning: selection of appropriate models, methods, libraries, etc.
- Software development
- Development of objective testing methods, testing, evaluation of results