Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB

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Teaching by Demonstrating - How Smart Assistive Systems can Learn from Users

2020 , Büttner, Sebastian , Peda, Andreas , Heinz, Mario , Röcker, Carsten

Projection-based assitive systems that guide users through assembly work are on their way to industrial application. Previous research work investigated how people can be supported with such systems. However, there has been little work on the question on how to generate and author sequential instructions for assitive systems. In this paper, we present a new concept and a prototypical implementation of an assitive system that can be taught by demonstrating an assembly process. By using a combination of RGB and depth cameras, we can generate an assembly instruction of Lego Duplo bricks based on the demonstration of a user. This generated manual can later on be used for assisting other users in the assembly process. By our prototype system, we show the technological feasibility of assistive systems that can learn from users.

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Exploring Users' Eye Movements when Using Projection-Based Assembly Assistive Systems

2020 , Heinz, Mario , Büttner, Sebastian , Röcker, Carsten

Projection-based assistive systems have shown to be a promising technology to support workers during manual assembly processes in industrial manufacturing by projecting instructions into the working area. While existing studies have investigated various aspects of these systems, little research has been conducted regarding the way in which the user accesses the provided instructions. In this paper we analyze the eye movements of users during the repeated execution of an assembly task at a projection-based assistive system in order to gain insights into the utilization of the presented instructions. For this purpose, we analyzed eye tracking recordings from a user study with 15 participants to investigate the sequences in which the respective instructions are observed by the users. The results show a significantly lower number of nonlinear gaze sequences as well as a significantly higher number of steps without observing the instructions during the repeated use of the assistive system. In addition, there was a significantly lower task completion time during repeated use of the assistive system.

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One-Hand Controller for Human-Drone Interaction - a Human-Centered Prototype Development

2020 , Büttner, Sebastian , Zaitoon, Rami , Heinz, Mario , Röcker, Carsten

Using remote control transmitters is a common way to control a drone. For the future, we envision drones that are intuitively controllable with new input devices. One possibility could be the use of one-hand controllers. Here, we present an exploration of using a 3-D mouse as a controller for human-drone interaction. We ran a pre-study that investigated the users' natural spatial mapping between controller and drone dimensions. Based on these results we developed our prototype that shows the feasibility of our concept. A series of flight tests were conducted and the mapping between controller and flight movements were iteratively improved. In this paper, we present our development process and the implementation of our prototype.

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Handling Work Complexity with AR/Deep Learning

2019 , Dhiman, Hitesh , Büttner, Sebastian , Röcker, Carsten , Reisch, Raphael

Complexity is a fundamental part of product design and manufacturing today, owing to increased demands for customization and advances in digital design techniques. Assembling and repairing such an enormous variety of components means that workers are cognitively challenged, take longer to search for the relevant information and are prone to making mistakes. Although in recent years deep learning approaches to object recognition have seen rapid advances, the combined potential of deep learning and augmented reality in the industrial domain remains relatively under explored. In this paper we introduce AR-ProMO, a combined hardware/software solution that provides a generalizable assistance system for identifying mistakes during product assembly and repair.

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Making Object Detection Available to Everyone - A Hardware Prototype for Semi-automatic Synthetic Data Generation

2020 , Besginow, Andreas , Büttner, Sebastian , Röcker, Carsten

The capabilities of object detection are well known, but many projects don't use them, despite potential benefit. Even though the use of object detection algorithms is facilitated through frameworks and publications, a big issue is the creation of the necessary training data. To tackle this issue, this work shows the design and evaluation of a prototype, which allows users to create synthetic datasets for object detection in images. The prototype is evaluated using YOLOv3 as the underlying detector and shows that the generated datasets are equally good in quality as manually created data. This encourages a wide adoption of object detection algorithms in different areas, since image creation and labeling is often the most time consuming step.

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