The author introduces Calibra, an open-source toolkit designed to analyze and ensure the integrity of robot-learning datasets. The tool aims to prevent wasted compute by identifying problematic data before training begins.

  • duplicate or redundant demos
  • frozen camera frames
  • jittery robot motion
  • calibration drift
  • corrupted or inconsistent data

Calibra provides dataset observability and coreset selection capabilities for robotics imitation learning, with a Hugging Face Space available for health checks.