In today's fast-paced industrial manufacturing and logistics landscape, turnover boxes play an indispensable role in material handling. Their depalletizing efficiency has become a critical factor in keeping the entire logistics chain running smoothly.
As automation technology advances rapidly, traditional manual depalletizing methods are increasingly inadequate, unable to meet the modern logistics industry's stringent demands for efficiency and precision.
Transfer Technology's intelligent integration of AI-powered 3D vision with robot arms delivers an efficient, stable, and flexible solution for turnover box depalletizing.
01 Project Challenges
Through continuous circulation, turnover boxes inevitably experience deformation, resulting in poor dimensional consistency—placing extremely high demands on 3D vision systems for precision and adaptability. Additionally, randomly stacked mixed materials inside containers, potential reflections, and overflow conditions all create significant interference for visual recognition.
Achieving efficient and stable depalletizing under these complex and variable conditions has become a major challenge in logistics automation.
02 Technical Highlights
Transfer Technology's AI-powered 3D vision depalletizing solution combines the Epic Eye D-L vision system and Epic Pro software with ABB robotic arms to achieve precise visual recognition and stable gripping, ensuring high efficiency and accuracy in depalletizing operations.
Workflow:
Once turnover boxes are transported to the designated position, the Siemens PLC automatically triggers the vision system to initiate the imaging sequence. The Epic Eye D-L vision system then captures high-resolution images of the topmost turnover boxes, acquiring detailed and clear point cloud data.
Next, Epic Pro software takes over, performing a series of precision processing steps on the point cloud data, including preprocessing, template matching, and pose correction. It outputs precise pose information and of turnover boxes, and based on specific requirements, calculates container dimensions, validates pallet patterns, and ultimately guides the robot to complete the depalletizing task with precision.
±1mm Recognition Accuracy
±3mm Picking Accuracy
The solution achieves recognition accuracy of less than ±1mm. Advanced imaging algorithms deliver high-quality imaging of thin-walled turnover boxes even under typical factory ambient lighting interference.
Picking performance is equally impressive, with precision less than ±3mm ensuring accurate robotic handling. The powerful machine vision software features built-in AI algorithms capable of handling tightly nested turnover boxes, poor dimensional consistency, and inverted orientations. Even challenging conditions like reflective contents or material overflow do not affect recognition performance.
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