1 citations · 1 across the 8 of their papers we have counts for
12 papers
Towards VLA-Dreamer: Refining VLA Behavior Using World Models
Parsa Mastouri Kashani, Jan-Gerrit Habekost, Stefan Wermter
Vision-Language-Action models (VLAs), while showing strong potential for robot control, require massive amounts of high-quality imitation learning data. Moreover, the absence of an…
MorphIK: Morphology-Conditioned Neural Inverse Kinematics for Unknown Robots
Lennart Clasmeier, Jan Gerrit Habekost, Cornelius Weber +1
Neural models can learn to generate various solutions to the inverse kinematics problem from data, but are usually limited to a single robot. We present MorphIK, a flow-matching mo…
SmoLSTM: A Compact Vision-Language-Action Model with Recurrent Memory that Persists
Jan-Gerrit Habekost, Parsa Mastouri Kashani, Connor Gäde +5
Vision-language-action models often predict actions from only the current observation, which can leave tasks involving object occlusion or visually identical objects ambiguous with…
When May I Help You? On The Effect of Proactivity on Group Human-Robot Collaboration
Thomas Vitry, Vanessa Maeder, Kieran von Valeburg +6
Robot initiative is a central challenge in multi-party human-robot collaboration. A robot that contributes without being addressed may provide timely support, but it may also disru…
Identifying the Unknown: Prompt-Free Open Vocabulary Anomaly Recognition for Robot-Object Interaction
Philipp Allgeuer, Jan-Gerrit Habekost, Stefan Wermter
Robots operating in real-world environments must in general be able to recognize previously unseen objects. As robotic systems move toward open-world autonomy, there is a growing,…
Towards Learning a Generalizable 3D Scene Representation from 2D Observations
Martin Gromniak, Jan-Gerrit Habekost, Sebastian Kamp +2
We introduce a Generalizable Neural Radiance Field approach for predicting 3D workspace occupancy from egocentric robot observations. Unlike prior methods operating in camera-centr…
Keypoint-based Diffusion for Robotic Motion Planning on the NICOL Robot
Lennart Clasmeier, Jan-Gerrit Habekost, Connor Gäde +2
We propose a novel diffusion-based action model for robotic motion planning. Commonly, established numerical planning approaches are used to solve general motion planning problems,…
Personalised Explanations in Long-term Human-Robot Interactions
Ferran Gebellí, Anaís Garrell, Jan-Gerrit Habekost +3
In the field of Human-Robot Interaction (HRI), a fundamental challenge is to facilitate human understanding of robots. The emerging domain of eXplainable HRI (XHRI) investigates me…
Shaken, Not Stirred: A Novel Dataset for Visual Understanding of Glasses in Human-Robot Bartending Tasks
Lukáš Gajdošech, Hassan Ali, Jan-Gerrit Habekost +3
Datasets for object detection often do not account for enough variety of glasses, due to their transparent and reflective properties. Specifically, open-vocabulary object detectors…
Inverse Kinematics for Neuro-Robotic Grasping with Humanoid Embodied Agents
Jan-Gerrit Habekost, Connor Gäde, Philipp Allgeuer +1
This paper introduces a novel zero-shot motion planning method that allows users to quickly design smooth robot motions in Cartesian space. A Bézier curve-based Cartesian plan is t…
CycleIK: Neuro-inspired Inverse Kinematics
Jan-Gerrit Habekost, Erik Strahl, Philipp Allgeuer +2
The paper introduces CycleIK, a neuro-robotic approach that wraps two novel neuro-inspired methods for the inverse kinematics (IK) task, a Generative Adversarial Network (GAN), and…
NICOL: A Neuro-inspired Collaborative Semi-humanoid Robot that Bridges Social Interaction and Reliable Manipulation
Matthias Kerzel, Philipp Allgeuer, Erik Strahl +4
Robotic platforms that can efficiently collaborate with humans in physical tasks constitute a major goal in robotics. However, many existing robotic platforms are either designed f…