Industrial robots have existed for decades, but most of them are “blind”—repeating pre-programmed trajectories with no awareness of their environment or variations in workpieces. When a workpiece position shifts slightly, when surface material differs somewhat, when assembly force needs fine-tuning—traditional industrial robots are at a loss.
VISME’s multimodal real interaction data is changing this reality. Here are three typical industrial application scenarios:
Scenario 1: Precision Assembly
On smartphone assembly lines, the installation of camera modules requires precision down to 0.01mm, while avoiding impact damage to sensitive components. Traditional vision-guided robots can only ensure positional accuracy—they cannot sense contact forces during assembly.
With vision-tactile joint training data provided by VISME, assembly robots can perceive resistance changes in real-time as modules are inserted. When resistance increases abnormally, the robot immediately stops and adjusts its posture to avoid component damage. When the robot senses that the module has “clicked” into place, it confirms successful assembly. Data-driven force-controlled assembly has increased yield rates from 92% to 99.5%.
Scenario 2: Complex Grasping
In logistics sorting scenarios, packages vary wildly in shape, size, and material—from rigid cardboard boxes to soft clothing, from光滑 plastic bags to rough woven sacks. Traditional suction-based grasping is sensitive to surface material and prone to dropping; traditional grippers lack force sensing and容易 crush items.
Using grasping models trained on thousands of real grasping samples collected by VISME, systems can take one “look” at an object, predict the optimal grasping strategy, and adjust force in real-time through tactile feedback upon contact. Success rates for grasping irregular soft packages have improved from 76% to 94%.
Scenario 3: Human-Robot Collaboration
In flexible production lines, robots work in close proximity with human workers. When a human hands over a part, the robot must perceive human intention—is it “handing over” or “taking back”? “Place gently” or “push firmly”?
VISME’s human-robot interaction datasets contain patterns of force variation at the moment of human-robot contact. Robots trained on this data can recognize human intentions, enabling natural and smooth collaboration—ensuring both safety and efficiency.
Data-Driven Industrial Intelligence
These scenarios are enabled not by more精密 hardware, but by smarter data. VISME is collaborating with multiple manufacturing industry leaders to transform real production scenarios into training素材 for AI. We believe that the core of Industry 4.0 is not automation, but intelligence—and the foundation of intelligence is real data.
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