Light geometry
Position, direction, size, and multiple sources
Technology
Controllable lighting for robot data
Transform real video into physically consistent lighting variants while motion, geometry, and task semantics stay aligned
How it works
One video enters, a lighting matrix comes out
Scene understanding, a relightable representation, and explicit lighting controls work as one engine
Interactive proof
Controlled light, unchanged task
Compare lighting conditions while scene structure, motion, and labels remain aligned
Control surface
Change the environment, not the task
Light character
Intensity, color, temperature, and softness
Deployment conditions
Day, night, side light, backlight, and mixed illumination
Training integrity
Temporal stability, preserved labels, and repeatable settings
Why it matters
Designed for model training, not visual effects
Explicit control
Recreate a condition instead of hoping a prompt repeats it
Physical response
Respect geometry, materials, shadows, and reflections
Video consistency
Keep lighting coherent across motion and changing viewpoints
Reusable labels
Preserve trajectories, poses, and task relationships
Start with your data
Bring us one real-world task
Share one task and the data you already have; we will shape the lighting matrix, delivery, and validation plan
Discuss a project