158 citations · 383 across the 25 of their papers we have counts for
27 papers
Learning Geometry-Aware Virtual Fixtures From Sparse Demonstrations
Maximilian Mühlbauer, Marcella Piacentino, Raffaella Mancino +10
In many teleoperation applications, collecting a large number of demonstrations as required for traditional probabilistic learning from demonstration (LfD) approaches may not be fe…
ErgoSurf: Ergodic Control for the Coverage of Unknown Surfaces
Stefan Schneyer, Timo Bachmann, Maged Iskandar +4
Contact-centric tasks on surfaces, ranging from inspection and cleaning to sanding and polishing, require robots to systematically cover the surface while maintaining stable contac…
CLASP: Language-Driven Robot Skill Selection and Composition using Task-Parameterized Learning
Markus Knauer, Valentin Gieraths, Tai Mai +4
Enabling robots to understand and execute tasks from natural language commands while maintaining data efficiency remains challenging. Foundation models such as vision-language-acti…
IROSA: Interactive Robot Skill Adaptation using Natural Language
Markus Knauer, Samuel Bustamante, Thomas Eiband +3
Foundation models have demonstrated impressive capabilities across diverse domains, while imitation learning provides principled methods for robot skill adaptation from limited dat…
Passive Variable Impedance For Shared Control
Maximilian Mühlbauer, Nepomuk Werner, Ribin Balachandran +4
Shared Control methods often use impedance control to track target poses in a robotic manipulator. The guidance behavior of such controllers is shaped by the used stiffness gains,…
MOMO: A framework for seamless physical, verbal, and graphical robot skill learning and adaptation
Markus Knauer, Edoardo Fiorini, Maximilian Mühlbauer +10
Industrial robot applications require increasingly flexible systems that non-expert users can easily adapt for varying tasks and environments. However, different adaptations benefi…