6 papers
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…
Communicating Robot's Intentions while Assisting Users via Augmented Reality
Chao Wang, Theodoros Stouraitis, Anna Belardinelli +2
This paper explores the challenges faced by assistive robots in effectively cooperating with humans, requiring them to anticipate human behavior, predict their actions' impact, and…
A Glimpse in ChatGPT Capabilities and its impact for AI research
Frank Joublin, Antonello Ceravola, Joerg Deigmoeller +3
Large language models (LLMs) have recently become a popular topic in the field of Artificial Intelligence (AI) research, with companies such as Google, Amazon, Facebook, Amazon, Te…
Understanding the Uncertainty Loop of Human-Robot Interaction
Jan Leusmann, Chao Wang, Michael Gienger +2
Recently the field of Human-Robot Interaction gained popularity, due to the wide range of possibilities of how robots can support humans during daily tasks. One form of supportive…
Explainable Human-Robot Training and Cooperation with Augmented Reality
Chao Wang, Anna Belardinelli, Stephan Hasler +3
The current spread of social and assistive robotics applications is increasingly highlighting the need for robots that can be easily taught and interacted with, even by users with…
Distilled Domain Randomization
Julien Brosseit, Benedikt Hahner, Fabio Muratore +2
Deep reinforcement learning is an effective tool to learn robot control policies from scratch. However, these methods are notorious for the enormous amount of required training dat…