Brain
VLA with Ego3D position encoding and adaptive action grids, pretrained on 1.1M real robot episodes. Multi-institutional research effort demonstrating spatial reasoning for cross-embodiment manipulation.
Foundation model · Maturity: Research · Open source
Machine-readable surfaces
- Markdown mirror: /brains/spatialvla.md
- RSS feed: /brains/spatialvla/feed.xml
- JSON-LD: embedded in this page’s head
- REST API: /v1/brains/5f5bb142-a08e-4f41-a576-8243ec4659bd
- Revision history: /brains/spatialvla/history
- Data documentation: /data
- Query this programmatically: Deploy MCP
Architecture
VLM + 3D spatial position encoding, adaptive action grids
Common questions
What is SpatialVLA?
VLA with Ego3D position encoding and adaptive action grids, pretrained on 1.1M real robot episodes. Multi-institutional research effort demonstrating spatial reasoning for cross-embodiment manipulation.
Is SpatialVLA open source?
Yes. SpatialVLA is recorded as open-source / open-weights on the DEPLOY registry, meaning model weights or source code are publicly available.
What type of AI is SpatialVLA?
SpatialVLA is a foundation model, built on a VLM + 3D spatial position encoding, adaptive action grids architecture on the DEPLOY registry.
What is SpatialVLA's maturity stage?
SpatialVLA is at the research stage on the DEPLOY maturity ladder. Research stage means active development without commercial deployments on file.
Which robots run on SpatialVLA?
No robot models on the DEPLOY registry are recorded as running SpatialVLA. DEPLOY wires brain-to-model connections only when the wiring is verifiable from primary sources; absence may reflect pre-deployment or unverified manufacturer claims.
Methodology: Claimed (not independently verified) · no sources on file · last reviewed 2026-08-23
Verification posture
Claimed (not independently verified)
Low confidence
Review state
Stable
Last reviewed 2026-08-23
Maturity + lifecycle
Maturity stage: research
The framework is documented at /methodology. Corrections at /corrections. Reviewer: DEPLOY editorial team.
Methodology surface for SpatialVLA.Canonical ID 5f5bb142-a08e-4f41-a576-8243ec4659bd