Online Fine-Tuning

Updating a pre-trained policy in real time using data from ongoing robot deployments. Online fine-tuning enables continuous improvement as the robot encounters new scenarios. Challenges include catastrophic forgetting, safe exploration during fine-tuning, and efficient computation of gradient updates on deployment hardware.

See this in practice: the Robotics Academy →