Customer-facing grocery store operations captured with dual camera system — Alia 360° sensor and Egocentric camera. Covers shopping aisles, checkout lanes, deli counters, produce sections, and self-checkout areas across multiple stores and time-of-day conditions.
Modalities 1–10 from the stack above
Back-of-store operations — receiving docks, cold storage, stockrooms, and restocking workflows. Captures the logistics side of grocery with forklift activity, pallet handling, and inventory management tasks.
Modalities 1–10 from the stack above
Action-centric dataset combining Alia 360° overhead capture with GoPro egocentric cameras on workers. Includes all 10 VLM modalities plus manually corrected hand pose, body pose and human to robot retargeted data — purpose-built for training Vision-Language-Action models.
All 13 modalities including action data
Backend logistics with full action annotation — receiving, stocking shelves, operating pallet jacks, and managing cold-chain inventory. Dual-stream capture enables training VLA models on the physical manipulation tasks behind grocery operations.
All 13 modalities including action data
Simulation-ready grocery environments and objects in Universal Scene Description (USD) format, built from DreamVu's 3D reconstructions. Drop directly into NVIDIA Isaac Sim or Omniverse for robot training, validation, and sim-to-real transfer.
DreamVu deploys to your facility with our Alia 360° capture rigs and full annotation pipeline. You get the same multi-layer annotation stack applied to your specific environment, operations, and use cases.