In the automotive industry, sheet metal parts are widely used for components like vehicle body shells and doors, 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 just 5 minutes, thereby driving industrial upgrading.

Conventional methods for loading and unloading stamped parts in the automotive industry are error-prone and inefficient, which impairs production efficiency and quality. To solve the pain point, DexForce launches the spatial and embodied intelligence suite, which leverages synthetic data to train models based on the DexVerse™ engine, to help customers quickly complete vision configuration, and enable robotic arms to accurately grasp stamped parts. The innovative solution streamlines loading and unloading processes, and injects strong momentum into the industry's intelligent transformation.

The loading and unloading of components in the automotive transmission system affects vehicle performance and production capacity. Traditional methods suffer from positioning deviations and inefficiencies. Empowered by the DexVerse™ engine, DexForce's spatial and embodied intelligence suite employs synthetic data to train models, which allows for rapid configuration and high-precision handling of robotic arms. DexForce aims to empower automakers to move towards intelligent and efficient production.

Vision guidance acts as a "precise navigation system" for the orderly loading of automotive aluminum castings, cutting through their complex geometries to accurately position randomly oriented aluminum billets. DexForce leverages the virtual-real integrated computing power to redefine production processes, and the embodied intelligence suite endows equipment with the adaptive "dexterous hands" to handle these tasks. Together, they break the efficiency ceiling of traditional loading, and are reshaping the ecosystem for precise workflow in automotive manufacturing.