Moving Beyond Traditional Depalletizing: How Transfer Technology’s AI+3D Vision Transforms the Depalletizing Process?

In today's fast-paced era of industrial manufacturing and logistics, totes and cases play an indispensable role in material circulation. Their depalletizing efficiency has become a key factor guaranteeing smooth operation of the entire logistics chain.

With the rapid advancement of automation technology, traditional manual depalletizing methods have gradually become inadequate, failing to meet the strict requirements for efficiency and precision in modern logistics.

Transfer Technology’s intelligent combination of AI+3D vision and robotic arms delivers an efficient, stable and flexible solution for tote and case depalletizing.

01 Project Challenges

After long-term cyclic usage, totes and cases are prone to deformation and poor dimensional consistency, placing extremely high requirements on the precision and adaptability of the 3D vision system. Besides, disorderly stacked goods inside containers, as well as possible reflection and material spillage, create considerable interference for visual recognition.

Achieving efficient and stable depalletizing under such complex and variable conditions remains a major challenge in logistics automation.

02 Technical Highlights

Transfer Technology’s AI+3D vision depalletizing solution adopts the Epic Eye D-L vision system and Epic Pro software, paired with an ABB robotic arm to realize accurate visual recognition and stable gripping, ensuring high efficiency and precision for depalletizing operations.

Workflow

Once totes and cases are conveyed to the designated station, the Siemens PLC automatically triggers the vision system to initiate scanning. The Epic Eye D-L vision system conducts high-resolution scanning of the top-layer containers and captures detailed, clear point cloud data.

Epic Pro software then processes the point cloud data through a series of precise procedures including preprocessing, template matching and pose correction. It accurately outputs container pose information, calculates container dimensions and verifies stacking patterns as needed, and ultimately guides the robot to complete depalletizing accurately.

Recognition Accuracy: ±1 mm

Gripping Accuracy: ±3 mm

The solution achieves a recognition accuracy of ±1 mm. Equipped with advanced imaging algorithms, it enables high-quality scanning of thin-walled totes and cases even amid ambient light interference commonly seen in factories.

It also delivers outstanding gripping performance with ±3 mm gripping accuracy to support precise robotic handling. Embedded with AI algorithms, the robust machine vision software can cope with closely fitted containers, inconsistent geometries and upside-down cases. Recognition will not be disrupted even if internal contents cause reflection or spillage.