Real-world variation
Displaced parts, new product specifications, equipment state changes and human–robot collaboration add variation across different materials, dimensions and precision requirements.
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DATA FOR REAL-WORLD WORK / 02
Manufacturing scenarios
Train for precision. Prepare for variation.
Explore data for parts picking, machine tending, component assembly, tool use and material transport.
Sample access depends on the selected dataset. Use a published sample link when available, or request a sample for evaluation.
The scenario
Train for precision. Prepare for variation.
Manufacturing scenarios cover production workshops, assembly stations, processing equipment and surrounding production areas. They capture repetitive operations at fixed stations alongside changing production conditions, following robots as they identify parts, interact with equipment, assemble components and move materials between workstations.
Operating environments
Production workshops, assembly stations, processing equipment and the areas connecting industrial workstations.
Tasks to learn
- 01Pick parts
- 02Load and unload machines
- 03Assemble components
- 04Use tools
- 05Inspect finished products
- 06Transport materials
Data and signals
Data may record object poses, motion trajectories, contact forces, equipment feedback and task outcomes throughout manufacturing operations.
Capabilities to develop
Support reliable grasping, precision assembly, anomaly detection and motion adjustment, with data for assessing robot capabilities within manufacturing workflows.
See the work in context.
Dedicated spaces for scene photography and task videos. Published media will show the environment and the actions captured.
Scenario image
Task demonstration video
Manufacturing
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Sample access depends on the selected dataset. Use a published sample link when available, or request a sample for evaluation.