79 citations · 105 across the 3 of their papers we have counts for
5 papers · 1 filter
Composing Dextrous Grasping and In-hand Manipulation via Scoring with a Reinforcement Learning Critic
Lennart Röstel, Dominik Winkelbauer, Johannes Pitz +2
In-hand manipulation and grasping are fundamental yet often separately addressed tasks in robotics. For deriving in-hand manipulation policies, reinforcement learning has recently…
A Learning-based Controller for Multi-Contact Grasps on Unknown Objects with a Dexterous Hand
Dominik Winkelbauer, Rudolph Triebel, Berthold Bäuml
Existing grasp controllers usually either only support finger-tip grasps or need explicit configuration of the inner forces. We propose a novel grasp controller that supports arbit…
Self-Contained Calibration of an Elastic Humanoid Upper Body Using Only a Head-Mounted RGB Camera
Johannes Tenhumberg, Dominik Winkelbauer, Darius Burschka +1
When a humanoid robot performs a manipulation task, it first makes a model of the world using its visual sensors and then plans the motion of its body in this model. For this, prec…
Combining Shape Completion and Grasp Prediction for Fast and Versatile Grasping with a Multi-Fingered Hand
Matthias Humt, Dominik Winkelbauer, Ulrich Hillenbrand +1
Grasping objects with limited or no prior knowledge about them is a highly relevant skill in assistive robotics. Still, in this general setting, it has remained an open problem, es…
Learning to Localize in New Environments from Synthetic Training Data
Dominik Winkelbauer, Maximilian Denninger, Rudolph Triebel
Most existing approaches for visual localization either need a detailed 3D model of the environment or, in the case of learning-based methods, must be retrained for each new scene.…