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Case Background

In the automotive industry, sheet metal parts are widely used for vehicle body shells, doors, and other components, crucial for ensuring structural stability and appearance formation. DexForce's spatial and embodied intelligence suite is set to empower the operations. By leveraging DexVerse™ engine and intelligent sensors to train models on synthetic data, the suite enables automakers to complete configurations efficiently and accurately in 5 minutes, thereby driving industrial upgrading.

Case Challenges

⦁ Heavy weight of sheet metal parts causes low efficiency of manual loading and potential safety risks.

⦁ Variety and easy deformation of sheet metal parts demands fast cycle time and high stability.

Case Video

Core Values

Recognition of Any Given Objects

Recognition of Any Given Objects

Supports recognizing various sheet metal parts, including symmetric and irregular-shaped ones, to enable rapid production capacity expansion.
Precise Grasping

Precise Grasping

Enabled by advanced vision algorithms that accurately locate sheet metal parts and guide robots for precise handling.

Product Features

High Energy for Robust Light Resistance

High Energy for Robust Light Resistance

Leveraging its high-energy laser, the camera offers exceptional ambient light resistance to ensure clear imaging of black and highly reflective workpieces despite complex environments.
Large Field of View with Extended Depth of Field

Large Field of View with Extended Depth of Field

Compared with traditional cameras, laser-empowered cameras have larger depth of field to meet the customer's needs for wider field of view.
Edge Computing for Reduced Host Load

Edge Computing for Reduced Host Load

Powered by NVIDIA Jetson Nano module, the camera boasts built-in powerful computing capabilities to realize independent camera control and point cloud analysis for imaging. Compared with traditional cameras, it operates faster and more stably while freeing up the customer's host computing resources.
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