Features
Physical world foundation model for robot control
Multi-task learning across manipulation, locomotion, and navigation
Simulation-to-real transfer with domain randomization
Hardware-agnostic deployment via unified API
Real-time perception and motion planning
Generative trajectory prediction
Zero-shot transfer to new environments
Safety constraints with conformal prediction
Model fine-tuning on custom tasks using few demonstrations
Integration with ROS 2 and industrial controllers
Cloud-based training infrastructure
Edge deployment on embedded systems
Unified omni-bodied AI brain for any robot type
Learns manipulation skills from human video demonstrations
Security/inspection robot navigation in hazardous environments
Mobile manipulation with grasping, handover, and navigation
Autonomous packing with precise dexterous manipulation
API abstraction for high-level task control
General-purpose physical world understanding
Scalable data solution via human video
Unstructured environment operation
Real-world value-focused applications (inspection, packing)
Handles mobile manipulation on wheeled platforms
Autonomous navigation in dangerous settings
Skill execution via API calls for app building
