Gemini Robotics
Google DeepMind
Embodied reasoning and action model family that brings Gemini capabilities into robotics through vision, language, and physical action.
Physical reasoning and instruction following
A closed reference point, but useful for tracking the VLA/embodied foundation model direction.
A model hub link is a declaration. Files, loadability, evaluation, and deployment are scored separately.
Model decision scorecard
Use-case scores and evidence confidence are separate; Unknown is not treated as failure.
Code, weights, and checkpoints
UnknownArtifact availability is unknown.
Loading and training reproducibility
UnknownNo verified loading configuration is available.
Training data requirements
UsefulRequired signal categories are declared; exact tensor and action interfaces still need verification.
Evaluation evidence
UsefulEvaluation focus is declared, but metrics are not independently verified.
Deployment readiness
UnknownHardware, latency, dependencies, and runtime loading are not yet verified.
Artifact facts and provenance
No metadata-verified artifact facts yet. Source links remain declarations only.
Loop signal demand
Signals this model family needs for training, evaluation, or failure mining.
Observation / ego video
observation
Language intent / task phase
language intent · Vision-language interaction data connected to executable robot skills · Generalization tests across objects, scenes, and task instructions · Physical reasoning and instruction following
Action / robot state
actions · Vision-language interaction data connected to executable robot skills · Action grounding under novel objects and scenes
Future state / dynamics
Generalization tests across objects, scenes, and task instructions · Safety, affordance, and failure feedback for physical-world deployment · Action grounding under novel objects and scenes
Feedback / correction / failure
feedback/failure · Safety, affordance, and failure feedback for physical-world deployment · Safety and recovery when affordance estimates are wrong
Sim-real / embodiment metadata
Vision-language interaction data connected to executable robot skills
Evaluation focus
- Physical reasoning and instruction following
- Action grounding under novel objects and scenes
- Safety and recovery when affordance estimates are wrong
Missing critical loop signals
Core signal demands are represented. Check quality, alignment, and access constraints.
Related catalog datasets
Ego-Exo4D
Synchronized first-person and third-person skilled activity
Exact action dimensions, control frequency, normalization, and camera mapping require interface verification.
Ego4D
Large-scale daily-life egocentric video
Exact action dimensions, control frequency, normalization, and camera mapping require interface verification.
EgoWorld
Bimanual manipulation in LeRobot format
Dataset license restricts commercial use.
OpenBot notes
- A closed reference point, but useful for tracking the VLA/embodied foundation model direction.
- Shows why OpenBot should not limit Catalog to robot data; human-centric interaction data can still support grounding and failure mining.