Pascal Meisner
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Learning a Generative Transition Model for Uncertainty-Aware Robotic\n Manipulation Open
Robot learning of real-world manipulation tasks remains challenging and time\nconsuming, even though actions are often simplified by single-step manipulation\nprimitives. In order to compensate the removed time dependency, we additionally\…
Self-Supervised Learning for Precise Pick-and-Place Without Object Model Open
Flexible pick-and-place is a fundamental yet challenging task within\nrobotics, in particular due to the need of an object model for a simple target\npose definition. In this work, the robot instead learns to pick-and-place\nobjects using …