3D random grabbing system
Product Center
The machine 3D disorderly grasping replaces the traditional tooling fixture, and is designed for the scattered and disorderly stacked workpieces, which can assist the robot to efficiently and accurately complete the 3D intelligent grasping, and well solve the problem of flexible chemical equipment.
High precision, high efficiency and high versatility are the most significant advantages of 3D visual positioning system.
Product details
3D random grabbing system
System specification
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High accuracy
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High frame clearing rate
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Strong flexibility
The machine 3D disorderly grasping replaces the traditional tooling fixture, and is designed for the scattered and disorderly stacked workpieces, which can assist the robot to efficiently and accurately complete the 3D intelligent grasping, and well solve the problem of flexible chemical equipment. High precision, high efficiency and high universality are the most significant advantages of 3D visual positioning system.
System composition
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3D industrial camera
Select the type and model of camera with corresponding field of view and accuracy according to the situation.
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Roboeye.AI
The component of vision scheme automatically generates AI model based on deep learning algorithm for recognition and location.
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controller
Visual scheme components.
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3D industrial robot
Different types of industrial robots are selected according to the workpiece weight and process range.
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Robot fixture
Design robot fixture according to workpiece shape and process.
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Automation station integration
In order to realize the process, the station is integrated with software and hardware.
Application scenarion
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01.
Robot 3D positioning, grasping and loading of multi variety workpieces.
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02.
Fast 3D positioning and grasping of objects on conveyor belt.
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03.
3D positioning and grasping of large objects.
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04.
Flexible 3D positioning and grasping of complex polyhedral workpiece.
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05.
3D positioning of robot assembly for large equipment.
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06.
Robot Cooperative 3D positioning and grasping between multiple processes.
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07.
3D positioning of disorderly incoming parts.
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08.
3D recognition and positioning of frame stacking objects.
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09.
3D recognition and positioning of incoming materials of spraying robot.
Core technology
| Object detection | Point cloud matching |
|---|---|
| AI model using simulated data (patent) | Original AI model (patent) |
| It does not need or only needs a small amount of annotation data, and the degree of automation of model making is high. | “ZERO” sample |
| Without the serious problem of over fitting of traditional deep learning algorithm, the anti-interference ability is improved. | It can effectively deal with and improve the recognition rate of cloud missing and thin parts. |
| High precision edge location through dynamic domain and shape prior knowledge modeling (patent) | The model can be generalized to any part without further training for different parts. |
| Through the automatic sample enhancement technology, the model can resist the unknown ambient light interference other than the situation contained in the training data. | |
| Through in-depth learning, model simplification and refining technology, model efficiency can be improved to a greater extent. | |
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