6 citations · 18 across the 14 of their papers we have counts for
17 papers
Uncertainty-driven Exploration Strategies for Online Grasp Learning
Yitian Shi, Philipp Schillinger, Miroslav Gabriel +4
Existing grasp prediction approaches are mostly based on offline learning, while, ignoring the exploratory grasp learning during online adaptation to new picking scenarios, i.e., o…
SA6D: Self-Adaptive Few-Shot 6D Pose Estimator for Novel and Occluded Objects
Ning Gao, Ngo Anh Vien, Hanna Ziesche +1
To enable meaningful robotic manipulation of objects in the real-world, 6D pose estimation is one of the critical aspects. Most existing approaches have difficulties to extend pred…
Model-free Grasping with Multi-Suction Cup Grippers for Robotic Bin Picking
Philipp Schillinger, Miroslav Gabriel, Alexander Kuss +2
This paper presents a novel method for model-free prediction of grasp poses for suction grippers with multiple suction cups. Our approach is agnostic to the design of the gripper a…
SyMFM6D: Symmetry-aware Multi-directional Fusion for Multi-View 6D Object Pose Estimation
Fabian Duffhauss, Sebastian Koch, Hanna Ziesche +2
Detecting objects and estimating their 6D poses is essential for automated systems to interact safely with the environment. Most 6D pose estimators, however, rely on a single camer…
Wasserstein Gradient Flows for Optimizing Gaussian Mixture Policies
Hanna Ziesche, Leonel Rozo
Robots often rely on a repertoire of previously-learned motion policies for performing tasks of diverse complexities. When facing unseen task conditions or when new task requiremen…
The e-Bike Motor Assembly: Towards Advanced Robotic Manipulation for Flexible Manufacturing
Leonel Rozo, Andras G. Kupcsik, Philipp Schillinger +9
Robotic manipulation is currently undergoing a profound paradigm shift due to the increasing needs for flexible manufacturing systems, and at the same time, because of the advances…