activity
20192023
most citedAutomatic Grasp Pose Generation for Parallel Jaw Grippers

1 citations · 2 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV2023★ 1 cited

Towards Packaging Unit Detection for Automated Palletizing Tasks

Markus Völk, Kilian Kleeberger, Werner Kraus +1

For various automated palletizing tasks, the detection of packaging units is a crucial step preceding the actual handling of the packaging units by an industrial robot. We propose…

cs.RO2021

Precise Object Placement with Pose Distance Estimations for Different Objects and Grippers

Kilian Kleeberger, Jonathan Schnitzler, Muhammad Usman Khalid +3

This paper introduces a novel approach for the grasping and precise placement of various known rigid objects using multiple grippers within highly cluttered scenes. Using a single…

cs.RO2021★ 1 cited

Automatic Grasp Pose Generation for Parallel Jaw Grippers

Kilian Kleeberger, Florian Roth, Richard Bormann +1

This paper presents a novel approach for the automatic offline grasp pose synthesis on known rigid objects for parallel jaw grippers. We use several criteria such as gripper stroke…

cs.CV2021

Investigations on Output Parameterizations of Neural Networks for Single Shot 6D Object Pose Estimation

Kilian Kleeberger, Markus Völk, Richard Bormann +1

Single shot approaches have demonstrated tremendous success on various computer vision tasks. Finding good parameterizations for 6D object pose estimation remains an open challenge…

cs.RO2021

Transferring Experience from Simulation to the Real World for Precise Pick-And-Place Tasks in Highly Cluttered Scenes

Kilian Kleeberger, Markus Völk, Marius Moosmann +4

In this paper, we introduce a novel learning-based approach for grasping known rigid objects in highly cluttered scenes and precisely placing them based on depth images. Our Placem…

cs.CV2020

Single Shot 6D Object Pose Estimation

Kilian Kleeberger, Marco F. Huber

In this paper, we introduce a novel single shot approach for 6D object pose estimation of rigid objects based on depth images. For this purpose, a fully convolutional neural networ…