How to make robots speed up and slow down on demand?

Robot manipulators need variable speed: fast transit, slow contact. Existing vision-language-action models learn one fixed speed from demos. TempoVLA adds a speed condition to the policy and augments training data by re-timing trajectories without breaking the motion logic. Real robot experiments show flexible speed control in both directions, with the augmentation also improving baseline performance through better data use.