Digital Twins in Robotics Development

A high-fidelity simulated copy of a real robot, kept in sync and used for far more than just training.

A digital twin is a simulated model of a specific physical robot (or system) kept detailed and accurate enough to meaningfully predict how the real thing will behave — distinct from a generic simulation used only for initial algorithm development.

What it's used for beyond training

Digital twins let engineers test software updates, plan maintenance, and diagnose unusual behavior against a virtual model before (or instead of) risking the physical robot, and can be updated continuously using real sensor data to stay accurate as the physical hardware wears or changes over time.

Why it's harder than it sounds

Keeping a simulated model closely matched to a real, physically degrading robot requires ongoing calibration and system identification — without that upkeep, a digital twin gradually drifts from reality and becomes less useful than a fresh, generic simulation would be.