Voxelmaps digitizes reality and makes it accessible for Physical AI — giving robots a live, high-accuracy model of the world exactly as it is.
Robotic Space Convergence
To operate safely and usefully, robots must connect World Space — 3D/4D geometry, semantics, change over time — with Task Space — actions, manipulation, interaction dynamics. The convergence creates Robotic Space.
3D/4D geometry, semantics, change over time
Actions, intent, manipulation, 40–200 DoF
Perception + navigation + embodiment, grounded in reality
Two Sides. One Mission.
World SpaceMulti-modal LiDAR + high-res imagery across street-level, aerial, pedestrian, indoor, and complex operational spaces. Built for AVs, digital twins, and robotics navigation.
Human SpaceDiverse, distributed, and global participant network across 12+ countries. From full-body motion capture to lived-in spaces, all natural, unscripted behavior.
SYMBO NET
A one-to-many reality capture network. Continuous mapping and refresh producing 4D map data — bridging physical reality and data demand with the most cost-effective operating model on the market.
Degrees of Freedom
As autonomy advances into higher DoF systems, data requirements grow non-linearly. The market needs far more dense, semantically rich, time-aware datasets than exist today.
X,Y translation + yaw. Constrained to ground.
X,Y,Z translation + roll/pitch/yaw. Free flight.
6-DoF base + many joints across arms, hands, legs, torso, head.
Use Cases
Replacing synthetic data with lived-in reality across homes and corporate offices.
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Fully natural, unscripted behavior captured via wearable cameras at the point of work.
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Multi-camera body positioning and scanning with rapid mobilization from outreach to capture.
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VR-gamer motion datasets with zero no-shows across all scheduled sessions.
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98% eligibility accuracy through strict automated screening and identity validation.
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