Andreas Kriegler

• Master of Science
• PhD Student at TU Wien

This review paper provides an overview of papers that have studied body movement mirroring and synchrony within the field of human-robot interaction. The papers included in this review cover system studies, which focus on evaluating the technical aspects of mirroring and synchrony robotic systems, and user studies, which focus on measuring particul...

Kuhn’s groundbreaking Structure divides scientific progress into four phases, the pre-paradigm period, normal science, scientific crisis and revolution. Most of the time a field advances incrementally, constrained and guided by a currently agreed upon paradigm. Creative phases emerge when phenomena occur which lack satisfactory explanation within t...

For mobile robots to be considered autonomous they must reach target locations in required pose, a procedure referred to as docking. Popular current solutions use LiDARs combined with sizeable docking stations but these systems struggle by incorrectly detecting dynamic obstacles. This paper instead proposes a vision-based framework for docking a mo...

A considerable amount of research is concerned with the challenging task of estimating three-dimensional (3D) pose and size for multi-object indoor scene configurations. Many existing models rely on a priori known object models, such as 3D CAD models and are therefore limited to a predefined set of object categories. This closed-set constraint limi...

Enhancing logistics vehicles on airport aprons with assistant and autonomous capabilities offers the potential to significantly increase safety and efficiency of operations. However, this research area is still underrepresented compared to other automotive domains, especially regarding available image data, which is essential for training and bench...

Visual semantic context describes the relationship between objects and their environment in images. Analyzing this context yields important cues for more holistic scene understanding. While visual semantic context is often learned implicitly, this work proposes a simple algorithm to obtain explicit priors and utilizes them in two ways: Firstly, irr...

The estimation of depth cues from a single image has recently emerged as an appealing alternative to depth estimation from stereo image pairs. The easy availability of these dense depth cues naturally triggers research questions, how depth images can be used to infer geometric object and view attributes. Furthermore, the question arises how the qua...

Despite their increasing demand for assistant and autonomous systems, the recent shift towards data-driven approaches has hardly reached aerial domains, partly due to a lack of specific training and test data. We introduce the Aircraft Context Dataset, a composition of two inter-compatible large-scale and versatile image datasets focus-ing on manne...

Localization using images is a fundamental problem in computer vision for autonomous systems. The information gained enables a high-level understanding of the environment for the mobile robot, which is much more in line with a person’s understanding of their surroundings. It is therefore a critical task for human-robot collaboration and enables rob...

Visual semantic context describes the relationship between objects and their environment in images. Analyzing this context yields important cues for more holistic scene understanding. Domains are an extension of semantic context across multiple images, specified by visual features and form the environment objects most commonly appear in. Humans nat...

To aid the high-level path-planning decisions of a mobile robot, it has to know not just where it is, but also to identify the type and specifics of that place. Customarily, a deep-learning model such as a convolutional neural network (CNN) is trained to classify the location from a video stream. However, a neural network requires fine-tuning and i...

To aid the high-level path-planning decisions of a mobile robot, the robotics system has to know not just where the robot is, but also to identify the type and specifics of that place. This is useful in industrial applications such as surveillance and warehousing robots to restrain them to certain environments, but also for human-robot collaboratio...

Basic Oxygen Steelmaking is the most popular method of steelmaking in the world. It uses Basic Oxygen Furnaces (BOFs for short) to blow pure oxygen at supersonic speed onto the surface of the molten pig iron to oxidize the carbon and create steel. During this process slag is being created, which fills the converter. When it cannot be contained in t...