7 citations · 8 across the 5 of their papers we have counts for
6 papers
Integrating Prior Observations for Incremental 3D Scene Graph Prediction
Marian Renz, Felix Igelbrink, Martin Atzmueller
3D semantic scene graphs (3DSSG) provide compact structured representations of environments by explicitly modeling objects, attributes, and relationships. While 3DSSGs have shown p…
Learning Contact Dynamics through Touching: Action-conditional Graph Neural Networks for Robotic Peg Insertion
Zongyao Yi, Joachim Hertzberg, Martin Atzmueller
We present a learnable physics-based model that predicts motion of the robot end effector and reaction force-torque in contact-rich manipulation. The model represents the end effec…
Uncertainty-Resilient Active Intention Recognition for Robotic Assistants
Juan Carlos Saborío, Marc Vinci, Oscar Lima +6
Purposeful behavior in robotic assistants requires the integration of multiple components and technological advances. Often, the problem is reduced to recognizing explicit prompts,…
Modern Neural Networks for Small Tabular Datasets: The New Default for Field-Scale Digital Soil Mapping?
Viacheslav Barkov, Jonas Schmidinger, Robin Gebbers +1
In the field of pedometrics, tabular machine learning is the predominant method for soil property prediction from remote and proximal soil sensing data, forming a central component…
Acting and Planning with Hierarchical Operational Models on a Mobile Robot: A Study with RAE+UPOM
Oscar Lima, Marc Vinci, Sunandita Patra +6
Robotic task execution faces challenges due to the inconsistency between symbolic planner models and the rich control structures actually running on the robot. In this paper, we pr…
Comprehensive Evaluation of Prototype Neural Networks
Philipp Schlinge, Steffen Meinert, Martin Atzmueller
Prototype models are an important method for explainable artificial intelligence (XAI) and interpretable machine learning. In this paper, we perform an in-depth analysis of a set o…