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Project Background

Driven by e-commerce prosperity and consumption upgrading, the traditional labor-intensive logistics model can no longer meet the demands of large-scale, high-efficiency cargo handling. The logistics industry urgently needs transformation and upgrading to enhance overall operational efficiency, reduce costs, and strengthen market competitiveness. By leveraging the DexVerse™ engine, DexForce's spatial and embodied intelligence suite empowers depalletizing and sorting operations with higher efficiency, intelligence, and precision, helping customers enhance their core competitiveness.

Project Challenges

⦁ Black and reflective surfaces of refractory bricks make high-quality imaging challenging.

⦁ Highly efficient on-site production is required, and grasping must be performed in sequence to avoid collision.

Case Video

Core Values

Complete Imaging of Highly Reflective Workpieces

Complete Imaging of Highly Reflective Workpieces

Guaranteed by the high-precision 3D camera that can generate high-fidelity images for black and reflective refractory bricks.
Precise Positioning

Precise Positioning

Enabled by advanced vision algorithms that accurately locate refractory bricks, sort accurately, and guide robots for successful grasping.

Product Recommendations

High Energy, More Anti-Interference

High Energy, More Anti-Interference

Based on the high-energy characteristics of lasers, the FINCH camera exhibits excellent anti-interference performance, enabling imaging of black, high-contrast components in complex environments
Large Field of View, Greater Depth of Field

Large Field of View, Greater Depth of Field

The laser beam has an exceptionally large depth of field range, offering greater depth of field compared to traditional optical systems, meeting customers' larger field of view requirements
Edge Computing, Smaller Burden

Edge Computing, Smaller Burden

Equipped with an NVIDIA Jetson Nano core, the camera has built-in powerful computing capabilities, independently achieving camera control and point cloud parsing imaging. Compared to traditional cameras, it is faster, more stable, and does not occupy the customer's host computing resources
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