Abstract: This paper investigates training better visual world models for robot manipulation, i.e., models that can predict future visual observations by conditioning on past frames and robot actions.

Abstract: Whole-body loco-manipulation for quadruped robots with arms remains a challenging problem, particularly in achieving multi-task control. To address this, we propose MLM, a reinforcement ...

ManiFlow is a visuomotor imitation learning policy for general robot manipulation that generates precise, high-dimensional, and dexterous actions from visual, language, and proprioceptive inputs. It ...