most citedLearning Task-Parameterized Skills from Few Demonstrations

3 citations · 3 across the 1 of their papers we have counts for

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cs.RO2024

Learning Deep Dynamical Systems using Stable Neural ODEs

Andreas Sochopoulos, Michael Gienger, Sethu Vijayakumar

Learning complex trajectories from demonstrations in robotic tasks has been effectively addressed through the utilization of Dynamical Systems (DS). State-of-the-art DS learning me…

cs.RO2024

Impact-Aware Bimanual Catching of Large-Momentum Objects

Lei Yan, Theodoros Stouraitis, João Moura +3

This paper investigates one of the most challenging tasks in dynamic manipulation -- catching large-momentum moving objects. Beyond the realm of quasi-static manipulation, dealing…

cs.RO2024

To Help or Not to Help: LLM-based Attentive Support for Human-Robot Group Interactions

Daniel Tanneberg, Felix Ocker, Stephan Hasler +6

How can a robot provide unobtrusive physical support within a group of humans? We present Attentive Support, a novel interaction concept for robots to support a group of humans. It…

cs.RO202472 cited

LaMI: Large Language Models for Multi-Modal Human-Robot Interaction

Chao Wang, Stephan Hasler, Daniel Tanneberg +5

This paper presents an innovative large language model (LLM)-based robotic system for enhancing multi-modal human-robot interaction (HRI). Traditional HRI systems relied on complex…

cs.RO2023

CoPAL: Corrective Planning of Robot Actions with Large Language Models

Frank Joublin, Antonello Ceravola, Pavel Smirnov +7

In the pursuit of fully autonomous robotic systems capable of taking over tasks traditionally performed by humans, the complexity of open-world environments poses a considerable ch…

cs.RO20231 cited

Predictive and Robust Robot Assistance for Sequential Manipulation

Theodoros Stouraitis, Michael Gienger

This paper presents a novel concept to support physically impaired humans in daily object manipulation tasks with a robot. Given a user's manipulation sequence, we propose a predic…