Multi-modal perception pipeline that fuses depth, RGB, and proprioception into structured scene understanding — the eyes, ears, and spatial awareness of embodied intelligence.
A camera captures pixels. A depth sensor measures distances. But embodied intelligence needs more than raw data — it needs to understand what it sees: where objects are in 3D space, what they are, how they relate to each other, and what they mean for the task at hand.
The SYNAPEX perception system fuses multiple sensor modalities into a unified scene representation that the brain modules can reason about, plan with, and act on. This is not just computer vision — it is the perceptual foundation of autonomous existence.
Our approach is fundamentally different from single-model vision systems. Perception is decomposed into specialised stages, each producing structured output that feeds the next — creating a pipeline that is interpretable, modular, and debuggable.
Seven layers of processing, each adding semantic richness to the raw input.
Each stage of the perception pipeline is published as a separate module in the SYNAPEX Lab. Researchers can use the full pipeline or pick individual modules — face recognition, object detection, depth estimation — for their own projects. Every module earns $SYNX for its creator.