High-fidelity robotic spatial-temporal datasets powering the next generation of simulation, perception, and autonomous intelligence.
High-fidelity spatial-temporal datasets powering the next generation of simulation, perception, and autonomous intelligence.
Dense, labeled objects and events captured from robotic platforms across diverse real-world environments.
Different modalities of robots in diverse environments: Humanoid, wheel-base, fixed-base, egocentric datasets.
Pre-processed for direct ingestion into major simulation pipelines and custom environments.
Generate high-fidelity digital twins of real-world spaces for testing and validation.
Train perception models on diverse, accurately labeled spatial-temporal data.
Pre-train world models with rich, multi-modal spatial-temporal sequences.
Join the waitlist to get early access to the platform.