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Models for warehouse picking
How to choose practical models for warehouse picking, tote transfer, SKU variability, and exception-heavy robot workflows.
Warehouse picking models should be judged by exception handling, SKU variability, and recovery speed, not only by clean benchmark accuracy.
Model priorities
- Fast recoveryBad picks and occlusion events happen constantly in production.
- Robust grasp adaptationPackaging variation breaks overly narrow policies.
- Operational observabilityTeams need clear metrics and easy failure slicing.
Good companions
Decision lens
If your warehouse task is narrow and repetitive, a smaller policy may outperform a heavier general model on deployment speed.
Need a picking model strategy?
We can help match picking workflows to data, model, and evaluation loops.
Every VLA here can be fine-tuned on your own demonstrations.