3 citations · 4 across the 5 of their papers we have counts for
6 papers · 1 filter
SpeedFolding: Learning Efficient Bimanual Folding of Garments
Yahav Avigal, Lars Berscheid, Tamim Asfour +2
Folding garments reliably and efficiently is a long standing challenge in robotic manipulation due to the complex dynamics and high dimensional configuration space of garments. An…
Learning a Generative Transition Model for Uncertainty-Aware Robotic Manipulation
Lars Berscheid, Pascal Meißner, Torsten Kröger
Robot learning of real-world manipulation tasks remains challenging and time consuming, even though actions are often simplified by single-step manipulation primitives. In order to…
Jerk-limited Real-time Trajectory Generation with Arbitrary Target States
Lars Berscheid, Torsten Kröger
We present Ruckig, an algorithm for Online Trajectory Generation (OTG) respecting third-order constraints and complete kinematic target states. Given any initial state of a system…
Self-supervised Learning for Precise Pick-and-place without Object Model
Lars Berscheid, Pascal Meißner, Torsten Kröger
Flexible pick-and-place is a fundamental yet challenging task within robotics, in particular due to the need of an object model for a simple target pose definition. In this work, t…
Robot Learning of Shifting Objects for Grasping in Cluttered Environments
Lars Berscheid, Pascal Meißner, Torsten Kröger
Robotic grasping in cluttered environments is often infeasible due to obstacles preventing possible grasps. Then, pre-grasping manipulation like shifting or pushing an object becom…
Improving Data Efficiency of Self-supervised Learning for Robotic Grasping
Lars Berscheid, Thomas Rühr, Torsten Kröger
Given the task of learning robotic grasping solely based on a depth camera input and gripper force feedback, we derive a learning algorithm from an applied point of view to signifi…