Alexander Bannat

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This paper presents a concept of a smart working environment designed to allow true joint-actions of humans and industrial robots. The proposed system perceives its environment with multiple sensor modalities and acts in it with an industrial robot manipulator to assemble capital goods together with a human worker. In combination with the reactive behavior(More)
Today's manufacturing and assembly systems have to be flexible to adapt quickly to an increasing number and variety of products, and changing market volumes. To manage these dynamics, several production concepts (e.g., flexible, reconfigurable, changeable or autonomous manufacturing and assembly systems) were proposed and partly realized in the past years.(More)
Traditional systems for digital assistance in manual assembly, e.g. optical displays at the work place, are inherently suboptimal for providing efficient and ergonomically feasible worker guidance. The display of sequential instructions does not offer an increase in productivity beyond a certain degree. Little situational support and the resulting(More)
We present the MuDiS project. The main goal of MuDiS is to develop a Multimodal Dialogue System that can be adapted quickly to a wide range of various scenarios. In this interdisciplinary project, we unite researchers from diverse areas, including computational linguistics, computer science, electrical engineering, and psychology. The different research(More)
This paper presents a new framework for multimodal data processing in real-time. This framework comprises modules for different input and output signals and was designed for human-human or human-robot interaction scenarios. Single modules for the recording of selected channels like speech, gestures or mimics can be combined with different output options(More)
In this paper we present a framework for realtime processing of multimodal data, which can be used for onand off-line processing of perceived data in interactions. We propose the use of a framework based on the Real-time Database (RTDB). This framework allows easy integration of input and output modules and thereby concentrating on the core functionality of(More)
In this paper a concept and its implementation of an ergonomic cognitive assistant system for supporting human workers at complex assembly tasks in industrial environments is introduced. Depending on the level of the userpsilas product knowledge this mixed-initiative system follows and gains knowledge from the human workerpsilas construction steps while it(More)
Efficient cooperation of humans and industrial robots is based on a common understanding of the task as well as the perception and understanding of the partner’s action in the next step. In this article, a hybrid assembly station is presented, in which an industrial robot can learn new tasks from worker instructions. The learned task is performed by both(More)
In this paper, we present a novel approach for multimodal interactions between humans and industrial robots. The application scenario is situated in a factory, where a human worker is supported by a robot to accomplish a given hybrid assembly scenario, that covers manual and automated assembly steps. The robot is acting as an assistant as well as a fully(More)
This article presents an integrated framework for multi-modal adaptive cognitive technical systems to guide, assist and observe human workers in complex manual assembly environments. The demand for highly flexible construction facilities obviously contradicts longer training and preparation phases of human workers. By giving context-aware building(More)