The virtual worlds where robots are trained
bbc.co.uk Sep 18, 2026

The virtual worlds where robots are trained

AI-summarised brief · reviewed before publication

A British Cambridge start‑up, Vsim, has demonstrated that its proprietary simulation platform can train a robot, named Freddo, to walk, recognize a plastic bottle and grasp it in just minutes, a task that rival systems reportedly require days to master. The training occurs in a virtual environment where millions of task iterations are run, producing an optimal policy that is then uploaded to the robot’s hardware. Vsim’s founders, Michelle Lu and Kier Storey, built the simulator to exploit modern GPUs, replacing legacy algorithms from the 1970s‑80s with a high‑performance architecture that can run tens of thousands of simulations in real time on the robot itself. This enables the robot to anticipate up to 20,000 possible future scenarios, allowing rapid adaptation to dynamic, unstructured settings such as homes or workplaces.

💡 Why It Matters

  • · Real‑time, on‑board simulation gives robots the foresight to react instantly to unpredictable environments, a capability that has long limited autonomous deployment.