• Publications
  • Influence
Max - A Multimodal Assistant in Virtual Reality Construction
TLDR
The overall architecture of Max is described with a focus on dialog and interaction management and the generation of synchronized multimodal utterances. Expand
Physical Human-Robot Interaction: Mutual Learning and Adaptation
TLDR
It is shown that this algorithm helps to improve the quality of the interaction between a robot and a human caregiver and two human-in-the-loop learning scenarios that are inspired by human parenting behavior are presented. Expand
Grasp Recognition with Uncalibrated Data Gloves - A Comparison of Classification Methods
TLDR
It is shown that a reasonably well to highly reliable recognition of grasp types can be achieved - depending on whether or not the glove user is among those training the classifier - even with uncalibrated data gloves, and the best performing classification methods are identified. Expand
Learning responsive robot behavior by imitation
TLDR
This paper simultaneously record the movements of two humans engaged in on-going interaction tasks and learn compact models of the interaction that can thereafter be used by a robot to engage in a similar interaction with a human partner. Expand
Grasp synthesis from low‐dimensional probabilistic grasp models
TLDR
A novel data‐driven animation method for the synthesis of natural looking human grasping that greatly reduces the high number of degrees of freedom of the human hand to a few dimensions in a continuous grasp space. Expand
FlurMax: An Interactive Virtual Agent for Entertaining Visitors in a Hallway
FlurMax, a virtual agent, inhabits a hallway at the University of Bielefeld. He resides in a wide-screen panel equipped with a video camera to track and interact with visitors using speech, gesture,Expand
Towards a Simulator for Imitation Learning with Kinesthetic Bootstrapping
TLDR
A physics based simulator that allows kinesthetic interactions between a human and a robot to be recorded, and later used for imitation learning, and a new scheme for robot motion learning based on kinesthetic bootstrapping is proposed. Expand
Grasp Recognition for Uncalibrated Data Gloves: A Machine Learning Approach
TLDR
It is shown that a reasonably good to highly reliable recognition of grasp types can be achieved depending on whether or not the glove user is among those training the classifiereven with uncalibrated data gloves, and the best performing classification methods for the recognition of various grasp types are identified. Expand
A system for learning continuous human-robot interactions from human-human demonstrations
TLDR
The effectiveness of the data-driven imitation learning system for learning human-robot interactions from human-human demonstrations on complex, sequential tasks is shown by presenting two applications involving collaborative human- robot assembly. Expand
Virtuelle Werkstatt: A platform for multimodal assembly in VR
TLDR
A knowledge-based approach for assembling CAD-based parts in VR is introduced and a framework for modeling multimodal interaction using gesture and speech is presented that facilitates its generic adaptation to scene-graph-based applications. Expand
...
1
2
3
4
5
...