Control
Real-Time Control
Real-time control is control computation subject to hard timing deadlines, where a late result is a wrong result. Robot servo loops typically run at 1 to 10 kHz, whole-body and impedance controllers at hundreds of hertz, and missed deadlines or jitter degrade stability margins. Achieving determinism requires real-time operating systems, deterministic fieldbuses such as EtherCAT, and careful isolation from non-deterministic workloads like vision or neural network inference.
Why it matters for physical AI
Learned components must coexist with hard real-time loops, so architectures that pair high-rate deterministic control with slower policy inference, connected through action chunking or setpoint streaming, are central to deploying neural policies on physical robots.
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.