Basics
This section introduces the basic information about the single-case carton depalletizing solution, including the applicability, unsupported functions and technical specifications.
Applicability
This section introduces the applicability of the single-case carton depalletizing solution from the aspects of carton types, project requirements, carton surface features, etc.
Carton Types
The table below illustrates the solution’s applicability to carton types.
| Feasible | Illustration | Not feasible | Illustration |
|---|---|---|---|
Regular paper cartons with a standard rectangular upper surface. |
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Flattened irregular rectangular cardboard, waste cartons, etc. |
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Project Requirements
The table below illustrates the solution’s applicability to project requirements.
| Feasible | Illustration | Not feasible | Illustration |
|---|---|---|---|
Single-Case Carton Depalletizing |
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Mixed-Case Carton Depalletizing |
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Single-Case Carton Palletizing |
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Mixed-Case Carton Palletizing |
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Carton Surface Features
The table below illustrates the solution’s applicability to carton surface features.
| Feasible | Illustration | Not feasible | Illustration |
|---|---|---|---|
Carton edges are clear. The carton’s surface can be either a single color or plain, , and it can feature patterns, text, strapping, or tapes. |
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Unable to clearly distinguish whether the cartons are single or multiple. For example, the carton body is divided by distinct patterns or stripes, or the cartons are closely packed together. |
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Carton Placement
The table below illustrates the solution’s applicability to carton placement.
| Feasible | Illustration | Not feasible | Illustration |
|---|---|---|---|
Individual carton sizes are moderate, that is, each carton occupies an appropriate proportion within the camera’s field of view. |
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Individual carton sizes are excessively large, with each carton occupying the entire camera field of view, which could potentially impact the effectiveness of deep learning recognition. |
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The camera is horizontally placed within the camera’s field of view, and the angle between the carton and the camera ranges from 0° to 45°. |
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The camera is inclined within the camera’s field of view, and the angle between the carton and the camera is greater than 45°. This may lead to deep learning recognition errors. |
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Workobject Carriers
The table below illustrates the solution’s applicability to workobject carriers.
| Feasible | Illustration | Not feasible | Illustration |
|---|---|---|---|
Cartons are placed on a pallet. |
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Cartons are placed in four-wall bins, containers, or turnover boxes, or there are other obstructions around the carton pallet. |
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Unsupported Functions
The single-case carton depalletizing solution does not support the following functions.
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Identification of the carton orientation. When the difference between the length and width of the carton is less than 20 mm, this solution does not support the identification of the carton’s orientation.
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Identification of the carton dimensions. When the carton is deformed, the vision recognition accuracy will be affected. Generally, the identification of carton dimensions is completed by the scanning equipment.
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Detection of damage on the carton’s surface. This solution does not currently support the defect detection function.