3 citations · 8 across the 6 of their papers we have counts for
5 papers · 1 filter
Learning Robotic Manipulation Policies from Point Clouds with Conditional Flow Matching
Eugenio Chisari, Nick Heppert, Max Argus +3
Learning from expert demonstrations is a promising approach for training robotic manipulation policies from limited data. However, imitation learning algorithms require a number of…
Imagine2touch: Predictive Tactile Sensing for Robotic Manipulation using Efficient Low-Dimensional Signals
Abdallah Ayad, Adrian Röfer, Nick Heppert +1
Humans seemingly incorporate potential touch signals in their perception. Our goal is to equip robots with a similar capability, which we term Imagine2touch. Imagine2touch aims to…
Interactive Imitation Learning in Robotics: A Survey
Carlos Celemin, Rodrigo Pérez-Dattari, Eugenio Chisari +7
Interactive Imitation Learning (IIL) is a branch of Imitation Learning (IL) where human feedback is provided intermittently during robot execution allowing an online improvement of…
Active Particle Filter Networks: Efficient Active Localization in Continuous Action Spaces and Large Maps
Daniel Honerkamp, Suresh Guttikonda, Abhinav Valada
Accurate localization is a critical requirement for most robotic tasks. The main body of existing work is focused on passive localization in which the motions of the robot are assu…
Doing Right by Not Doing Wrong in Human-Robot Collaboration
Laura Londoño, Adrian Röfer, Tim Welschehold +1
As robotic systems become more and more capable of assisting humans in their everyday lives, we must consider the opportunities for these artificial agents to make their human coll…