3 citations · 3 across the 4 of their papers we have counts for
4 papers
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…
TrueRMA: Learning Fast and Smooth Robot Trajectories with Recursive Midpoint Adaptations in Cartesian Space
Jonas C. Kiemel, Pascal Meißner, Torsten Kröger
We present TrueRMA, a data-efficient, model-free method to learn cost-optimized robot trajectories over a wide range of starting points and endpoints. The key idea is to calculate…
Referencing between a Head-Mounted Device and Robotic Manipulators
David Puljiz, Katharina S. Riesterer, Björn Hein +1
Having a precise and robust transformation between the robot coordinate system and the AR-device coordinate system is paramount during human-robot interaction (HRI) based on augmen…
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…