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In this paper we present SMART-FACTORY, a setup for a research and teaching facility in industrial robotics that is based on the RoboCup Logistics League. It is driven by the need for developing and applying solutions for digital production. Digitization receives constantly increasing attention in many areas, especially in industry. The common theme is to make things smart by using intelligent computer technology. Especially in the last decade there have been many attempts to improve existing processes in factories, for example, in production logistics, also with deploying cyber-physical systems. An initiative that explores challenges and opportunities for robots in such a setting is the RoboCup Logistics League. Since its foundation in 2012 it is an international effort for research and education in an intra-warehouse logistics scenario. During seven years of competition a lot of knowledge and experience regarding autonomous robots was gained. This knowledge and experience shall provide the basis for further research in challenges of future production. The focus of our SMART-FACTORY is to create a stimulating environment for research on logistics robotics, for teaching activities in computer science and electrical engineering programmes as well as for industrial users to study and explore the feasibility of future technologies. Building on a very successful history in the RoboCup Logistics League we aim to provide stakeholders with a dedicated facility oriented at their individual needs.
In this paper we report on an architecture for a self-driving car that is based on ROS2. Self-driving cars have to take decisions based on their sensory input in real-time, providing high reliability with a strong demand in functional safety. In principle, self-driving cars are robots. However, typical robot software, in general, and the previous version of the Robot Operating System (ROS), in particular, does not always meet these requirements. With the successor ROS2 the situation has changed and it might be considered as a solution for automated and autonomous driving. Existing robotic software based on ROS was not ready for safety critical applications like self-driving cars. We propose an architecture for using ROS2 for a self-driving car that enables safe and reliable real-time behaviour, but keeping the advantages of ROS such as a distributed architecture and standardised message types. First experiments with an automated real passenger car at lower and higher speed-levels show that our approach seems feasible for autonomous driving under the necessary real-time conditions.
A review of guidelines and best practices for subsonic aerodynamic simulations using RANS CFD
(2019)
A research framework for human aspects in the internet of production: an intra-company perspective
(2020)
Digitalization in the production sector aims at transferring concepts and methods from the Internet of Things (IoT) to the industry and is, as a result, currently reshaping the production area. Besides technological progress, changes in work processes and organization are relevant for a successful implementation of the “Internet of Production” (IoP). Focusing on the labor organization and organizational procedures emphasizes to consider intra-company factors such as (user) acceptance, ethical issues, and ergonomics in the context of IoP approaches. In the scope of this paper, a research approach is presented that considers these aspects from an intra-company perspective by conducting studies on the shop floor, control level and management level of companies in the production area. Focused on four central dimensions—governance, organization, capabilities, and interfaces—this contribution presents a research framework that is focused on a systematic integration and consideration of human aspects in the realization of the IoP.
A platform technology for the automated reaction control in magnetizable micro-fluidic droplets
(2014)
This paper addresses the pixel based classification of three dimensional objects from arbitrary views. To perform this task a coding strategy, inspired by the biological model of human vision, for pixel data is described. The coding strategy ensures that the input data is invariant against shift, scale and rotation of the object in the input domain. The image data is used as input to a class of self organizing neural networks, the Kohonen-maps or self-organizing feature maps (SOFM). To verify this approach two test sets have been generated: the first set, consisting of artificially generated images, is used to examine the classification properties of the SOFMs; the second test set examines the clustering capabilities of the SOFM when real world image data is applied to the network after it has been preprocessed to be invariant against shift, scale and rotation. It is shown that the clustering capability of the SOFM is strongly dependant on the invariance coding of the images.
A novel solar sterilization and water destillation system : experiment and thermodynamic analysis
(1991)
There are different types of games that try to make use of the motivation of a gaming situation in learning contexts. This paper introduces the new terminology ‘Competence Developing Game’ (CDG) as an umbrella term for all games with this intention. Based on this new terminology, an assessment framework has been developed and validated in scope of an empirical study. Now, all different types of CDGs can be evaluated according to a defined and uniform set of assessment criteria and, thus, are comparable according to their characteristics and effectiveness.
A New Class of Biosensors Based on Tobacco Mosaic Virus and Coat Proteins as Enzyme Nanocarrier
(2016)
This article introduces a new maritime search and rescue system based on S-band illumination harmonic radar (HR). Passive and active tags have been developed and tested attached to life jackets and a rescue boat. This system was able to detect and range the active tags up to a range of 5800 m in tests on the Baltic Sea with an antenna input power of only 100 W. All electronic GHz components of the system, excluding the S-band power amplifier, were custom developed for this purpose. Special attention is given to the performance and conceptual differences between passive and active tags used in the system and integration with a maritime X-band navigation radar is demonstrated.
In addition to very high safety and reliability requirements, the design of internal combustion engines (ICE) in aviation focuses on economic efficiency. The objective must be to design the aircraft powertrain optimized for a specific flight mission with respect to fuel consumption and specific engine power. Against this background, expert tools provide valuable decision-making assistance for the customer. In this paper, a mathematical calculation model for the fuel consumption of aircraft ICE is presented. This model enables the derivation of fuel consumption maps for different engine configurations. Depending on the flight conditions and based on these maps, the current and the integrated fuel consumption for freely definable flight emissions is calculated. For that purpose, an interpolation method is used, that has been optimized for accuracy and calculation time. The mission boundary conditions flight altitude and power requirement of the ICE form the basis for this calculation. The mathematical fuel consumption model is embedded in a parent program. This parent program presents the simulated fuel consumption by means of an example flight mission for a representative airplane. The focus of the work is therefore on reproducing exact consumption data for flight operations. By use of the empirical approaches according to Gagg-Farrar [1] the power and fuel consumption as a function of the flight altitude are determined. To substantiate this approaches, a 1-D ICE model based on the multi-physical simulation tool GT-Suite® has been created. This 1-D engine model offers the possibility to analyze the filling and gas change processes, the internal combustion as well as heat and friction losses for an ICE under altitude environmental conditions. Performance measurements on a dynamometer at sea level for a naturally aspirated ICE with a displacement of 1211 ccm used in an aviation aircraft has been done to validate the 1-D ICE model. To check the plausibility of the empirical approaches with respect to the fuel consumption and performance adjustment for the flight altitude an analysis of the ICE efficiency chain of the 1-D engine model is done. In addition, a comparison of literature and manufacturer data with the simulation results is presented.
Since fluid-structure interaction within the finite-element method is state of the art in many engineering fields, this method is used in voice analysis. A quasi two-dimensional model of the vocal folds including the ventricular folds is presented. First results of self-sustained vocal fold oscillation are presented and possibilities as well as limitations are discussed.
Achieving the 17 Sustainable Development Goals (SDGs) set by the United Nations (UN) in 2015 requires global collaboration between different stakeholders. Industry, and in particular engineers who shape industrial developments, have a special role to play as they are confronted with the responsibility to holistically reflect sustainability in industrial processes. This means that, in addition to the technical specifications, engineers must also question the effects of their own actions on an ecological, economic and social level in order to ensure sustainable action and contribute to the achievement of the SDGs. However, this requires competencies that enable engineers to apply all three pillars of sustainability to their own field of activity and to understand the global impact of industrial processes. In this context, it is relevant to understand how industry already reflects sustainability and to identify competences needed for sustainable development.
Innovative interplanetary deep space missions, like a main belt asteroid sample
return mission, require ever larger velocity increments (∆V s) and thus ever
more demanding propulsion capabilities. Providing much larger exhaust velocities than chemical high-thrust systems, electric low-thrust space-propulsion
systems can significantly enhance or even enable such high-energy missions. In
1995, a European-Russian Joint Study Group (JSG) presented a study report
on “Advanced Interplanetary Missions Using Nuclear-Electric Propulsion”
(NEP). One of the investigated reference missions was a sample return (SR)
from the main belt asteroid (19) Fortuna. The envisaged nuclear power plant,
Topaz-25, however, could not be realized and also the worldwide developments
in space reactor hardware stalled. In this paper, we investigate, whether such
a mission is also feasible using a solar electric propulsion (SEP) system and
compare our SEP results to corresponding NEP results.
Finding a good system topology with more than a handful of components is a
highly non-trivial task. The system needs to be able to fulfil all expected load cases, but at the
same time the components should interact in an energy-efficient way. An example for a system
design problem is the layout of the drinking water supply of a residential building. It may be
reasonable to choose a design of spatially distributed pumps which are connected by pipes in at
least two dimensions. This leads to a large variety of possible system topologies. To solve such
problems in a reasonable time frame, the nonlinear technical characteristics must be modelled
as simple as possible, while still achieving a sufficiently good representation of reality. The
aim of this paper is to compare the speed and reliability of a selection of leading mathematical
programming solvers on a set of varying model formulations. This gives us empirical evidence
on what combinations of model formulations and solver packages are the means of choice with the current state of the art.
The number of case studies focusing on hybrid-electric aircraft is steadily increasing, since these configurations are thought to lead to lower operating costs and environmental impact than traditional aircraft. However, due to the lack of reference data of actual hybrid-electric aircraft, in most cases, the design tools and results are difficult to validate. In this paper, two independently developed approaches for hybrid-electric conceptual aircraft design are compared. An existing 19-seat commuter aircraft is selected as the conventional baseline, and both design tools are used to size that aircraft. The aircraft is then re-sized under consideration of hybrid-electric propulsion technology. This is performed for parallel, serial, and fully-electric powertrain architectures. Finally, sensitivity studies are conducted to assess the validity of the basic assumptions and approaches regarding the design of hybrid-electric aircraft. Both methods are found to predict the maximum take-off mass (MTOM) of the reference aircraft with less than 4% error. The MTOM and payload-range energy efficiency of various (hybrid-) electric configurations are predicted with a maximum difference of approximately 2% and 5%, respectively. The results of this study confirm a correct formulation and implementation of the two design methods, and the data obtained can be used by researchers to benchmark and validate their design tools.