Perception
Object-Centric Representation
An object-centric representation is a scene encoding structured as a set of discrete object entities, each with its own features such as position, pose, extent, and appearance, rather than a single global feature vector or raw pixels. Approaches range from unsupervised slot-based models like Slot Attention to detector-derived object tokens consumed by manipulation policies.
Why it matters for physical AI
Factoring scenes into objects supports compositional generalization: a policy that reasons over object slots can transfer skills across novel arrangements and distractors more readily than pixel-level policies.
Build physical AI
Put these concepts to work on real hardware
Axol is a dual-arm robot built for physical AI — teleoperate it, collect demonstrations, and deploy learned policies out of the box.