NTNU – Application of 3D Machine Vision (TPK4850)

In this master course “experts in team” the scope is defined to:

“investigate new strategies, techniques and management, which lead to development of ecological and practical 3D machine vision systems in a total deferent way than traditional ones”

Read more @ NTNU: Application-of-3d-machine-vision-tpk4850

The course describes the following Scorpion 3D Stinger based system for

3D pizza sorting system

3D Pizza sorting system
The modular system comprises a conveyor, an ejector unit, machine vision hardware and software. The system is designed to meet the ip-grades and wash down requirements of the food industry. The following core functions describe the system:  Locate the pizza, measure the diameter, thickness profile and edge defects. Based on the measurements the user can set up the sorting criteria in a user friendly graphical user interface. The capacity of an installed system is 7200 pizzas per hour at a conveyor speed of 0.5 – 1.0 m/s. The system handles multiple and different sizes through a flexible recipe system. The diameter resolution is 0.5 mm and the height resolution is 0.2 mm.

3d image data

The 3D image data is used to accurately measure the height of the products in different regions of the surface. Local minima and maxima are localised.

The machine is based on the same powerful Scorpion Vision Software that has been at the heart of many automatic inspection systems used in manufacturing industries. Intended to reduce wastage and improve quality, the system uses a series of cameras to build a 3D profile of each product.

3D bin picking solution

Norwegian R&D project AutoCast developes leading edge 3D bin picking solution for the casting industry.

3D bin picking solution for the casting industry.

The leading Norwegian manufactures of castings need new technology to meet the international competition and the environment-, health- and safety requirements. This implies a considerable emphasis on the development of new technology to enhance the use of automation and robotics in the foundries. The small series production does not allow for unique solutions for individual parts. The main challenge is therefore to develop generic solutions that can be used on several different parts or families of parts.

Considerable focus on R & D has put the foundry industry in a leading position regarding casting- and materials technology. However, high salary costs and lack of working resources has created a need for further development of technology within automation and robotics. The Norwegian foundry industry has put their resources together through a R&D project, called “AutoCast” in order to focus on this development. The goal is to develop state of the art technology that ensures competitiveness of the Norwegian foundry industry.

Autocast project

AutoCast started in 2008 and is going to run for four years. The total budget is 5 MEuro. The project is supported by the Norwegian Research Council.

Tordivel AS, the company behind Scorpion Vision Software, is chosen as the 3D Machine Vision Partner for the AutoCast project.

In 2005 Tordivel decided to move Scorpion from a robust and proven 3D platform. The development has been organized in several R&D projects. The EU-CRAFT consortium 3DMulticam has developed a platform for 3D underwater metrology while the Auto3D project sponsored by the Norwegian Research Council has focused on creating a low-cost complete framework for 3D Machine Vision including stereo-vision, stripe light, 3D visualization, 3D references, doing 3D in 2D images and true 3D processing in point cloud.

Scenarios

The following scenarios must be handled in the AutoCast project:

  • Identification and location on a conveyor
  • Segmentation and 6 DOF location in a Bin

To solve the 3D Bin Picking solution it was obvious that a 3D machine vision solution was needed. After evaluating stripe light, 3D laser scanners and stereo vision, a solution based on three GigE cameras and 3D stereo vision was selected.

The reason for selecting this solution was the following:

  • Fast – a part is located in less than 1 second
  • Works even if objects are moving on a conveyor
  • Low component cost
  • Robust and reliable with 3 cameras
  • Accuracy

The 3D machine vision technology developed in the Norwegian AutoCast R&D project will keep the Norwegian foundry industry in a leading position regarding casting and material handling. The 3D machine vision part is based on Scorpion Vision Software, off-the-shelf software from Tordivel AS. This concept for accurate, low-cost 3D Bin Picking can be used in a vast number of industries

 

 

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