23 citations · 27 across the 14 of their papers we have counts for
15 papers
Co-VLA: Consensus-based Federated Training for Vision-Language-Action Models
Haolong Li, Guner Dilsad Er, Michael Muehlebach +1
Vision-language-action models (VLAs) have emerged as a promising paradigm for general-purpose robot learning, with performance improving as models and datasets scale. Scaling robot…
Learning Action-Conditional and Object-Centric Gaussian Splatting World Models for Rigid Objects
Jens U. Kreber, Lukas Mack, Joerg Stueckler
World models enable intelligent agents to predict the consequences of their actions on the environment. In this paper, we propose Multi Rigid Object Gaussian World Model (MRO-GWM),…
Guided Diffusion by Optimized Loss Functions on Relaxed Parameters for Inverse Material Design
Jens U. Kreber, Christian Weißenfels, Joerg Stueckler
Inverse design problems are common in engineering and materials science. The forward direction, i.e., computing output quantities from design parameters, typically requires running…
ISyHand: A Dexterous Multi-finger Robot Hand with an Articulated Palm
Benjamin A. Richardson, Felix Grüninger, Lukas Mack +2
The rapid increase in the development of humanoid robots and customized manufacturing solutions has brought dexterous manipulation to the forefront of modern robotics. Over the pas…
Guiding Diffusion-Based Articulated Object Generation by Partial Point Cloud Alignment and Physical Plausibility Constraints
Jens U. Kreber, Joerg Stueckler
Articulated objects are an important type of interactable objects in everyday environments. In this paper, we propose PhysNAP, a novel diffusion model-based approach for generating…
Visuo-Tactile Object Pose Estimation for a Multi-Finger Robot Hand with Low-Resolution In-Hand Tactile Sensing
Lukas Mack, Felix Grüninger, Benjamin A. Richardson +3
Accurate 3D pose estimation of grasped objects is an important prerequisite for robots to perform assembly or in-hand manipulation tasks, but object occlusion by the robot's own ha…
Learning a Terrain- and Robot-Aware Dynamics Model for Autonomous Mobile Robot Navigation
Jan Achterhold, Suresh Guttikonda, Jens U. Kreber +2
Mobile robots should be capable of planning cost-efficient paths for autonomous navigation. Typically, the terrain and robot properties are subject to variations. For instance, pro…
Incremental Few-Shot Adaptation for Non-Prehensile Object Manipulation using Parallelizable Physics Simulators
Fabian Baumeister, Lukas Mack, Joerg Stueckler
Few-shot adaptation is an important capability for intelligent robots that perform tasks in open-world settings such as everyday environments or flexible production. In this paper,…
Attention Normalization Impacts Cardinality Generalization in Slot Attention
Markus Krimmel, Jan Achterhold, Joerg Stueckler
Object-centric scene decompositions are important representations for downstream tasks in fields such as computer vision and robotics. The recently proposed Slot Attention module,…
Physics-Based Rigid Body Object Tracking and Friction Filtering From RGB-D Videos
Rama Krishna Kandukuri, Michael Strecke, Joerg Stueckler
Physics-based understanding of object interactions from sensory observations is an essential capability in augmented reality and robotics. It enables to capture the properties of a…
Online Calibration of a Single-Track Ground Vehicle Dynamics Model by Tight Fusion with Visual-Inertial Odometry
Haolong Li, Joerg Stueckler
Wheeled mobile robots need the ability to estimate their motion and the effect of their control actions for navigation planning. In this paper, we present ST-VIO, a novel approach…
Context-Conditional Navigation with a Learning-Based Terrain- and Robot-Aware Dynamics Model
Suresh Guttikonda, Jan Achterhold, Haolong Li +2
In autonomous navigation settings, several quantities can be subject to variations. Terrain properties such as friction coefficients may vary over time depending on the location of…
Black-Box vs. Gray-Box: A Case Study on Learning Table Tennis Ball Trajectory Prediction with Spin and Impacts
Jan Achterhold, Philip Tobuschat, Hao Ma +3
In this paper, we present a method for table tennis ball trajectory filtering and prediction. Our gray-box approach builds on a physical model. At the same time, we use data to lea…
Learning-based Relational Object Matching Across Views
Cathrin Elich, Iro Armeni, Martin R. Oswald +2
Intelligent robots require object-level scene understanding to reason about possible tasks and interactions with the environment. Moreover, many perception tasks such as scene reco…
Visual-Inertial Odometry with Online Calibration of Velocity-Control Based Kinematic Motion Models
Haolong Li, Joerg Stueckler
Visual-inertial odometry (VIO) is an important technology for autonomous robots with power and payload constraints. In this paper, we propose a novel approach for VIO with stereo c…