This process is a demo for shape recognition and product sorting automation utilizing 2D vision and a deep learning algorithm (Instance Segmentation).
Because it performs tasks by recognizing product positions and types in real-time using 2D vision, it can automatically recognize and work even if product positions or types change.
Components
| Robot | Robot Indy7: 6-axis collaborative robot, payload 7kg, maximum reach 1.3m, weight 28kg, repeatability: ± 0.1 mm |
|---|
Workflow
| STEP 1. | Workpiece moves to a designated position on a conveyor belt. |
|---|---|
| STEP 2. | Shape recognition of the object through deep learning. |
| STEP 3. | Pick and place of the workpiece |
※ The content provided by Marosol is protected under U.S. and Canadian copyright and intellectual property laws. Unauthorized reproduction, distribution, or use of this content is strictly prohibited.
Shape Recognition and Sorting Automation using Neuromeka Indy7 and IndyEye
- Implementing Company
- Please log in to view
- Estimated Project Duration
- 0week
- Robot Model
- -












