LABOR AND PROCESS EFFICIENCY THROUGH AUTONOMOUS MACHINE VISION GUIDED ROBOTIC LOADING ON FOOD MANUFACTURING LINES

This proposal aims to develop machine vision-guided technology to solve the loading challenges and enable smart agricultural/food manufacturing. We will use a blue crab processing line as example to demonstrate our novel techniques, which can be transferred to other agricultural materials. Specific tasks are: 1) to develop a laser based 3D vision technique to obtain topography of on-line materials. 2) to develop deep learning methods to recognize morphological features of objects and generate coordinates for robotic picking and loading. 3) to develop control schemes to pick up on-line materials and load them in the correct orientation. 4) to conduct tests to verify real world performance and demonstrate to the stakeholders. The outcome of this project will be automated loading technology for food manufacturing lines. The technology will be scalable to other food and agricultural commodities and engineering applications for food manufacturing automation.