Resolving uncertainty with VLMs and conformal prediction
Vision-Language-Model planning with uncertainty quantified via conformal prediction, executed by an imitation learning policy.
A Vision-Language Model is employed for robot planning, and the uncertainty of its responses is quantified using conformal prediction. The resulting plans are executed by an imitation learning policy, and a user interface was developed to facilitate interaction with a real robot.