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For a wide acceptance of E-Mobility, a well-developed charging infrastructure is needed. Conductive charging stations, which are today’s state of the art, are of limited suitability for urbanised areas, since they cause a significant diversification in townscape. Furthermore, they might be destroyed by vandalism. Besides for those urbanistic reasons, inductive charging stations are a much more comfortable alternative, especially in urbanised areas. The usage of conductive charging stations requires more or less bulky charging cables. The handling of those standardised charging cables, especially during poor weather conditions, might cause inconvenience, such as dirty clothing etc. Wireless charging does not require visible and vandalism vulnerable charge sticks. No wired connection between charging station and vehicle is needed, which enable the placement below the surface of parking spaces or other points of interest. Inductive charging seems to be the optimal alternative for E-Mobility, as a high power transfer can be realised with a manageable technical and financial effort. For a well-accepted and working public charging infrastructure in urbanised areas it is essential that the infrastructure fits the vehicles’ needs. Hence, a well-adjusted standardisation of the charging infrastructure is essential. This is carried out by several IEC (International Electrotechnical Commission) and national standardisation committees. To ensure an optimised technical solution for future’s inductive charging infrastructures, several field tests had been carried out and are planned in near future.
We present a robotic tool that autonomously follows a conversation to enable remote presence in video conferencing. When humans participate in a meeting with the help of video conferencing tools, it is crucial that they are able to follow the conversation both with acoustic and visual input. To this end, we design and implement a video conferencing tool robot that uses binaural sound source localization as its main source to autonomously orient towards the currently talking speaker. To increase robustness of the acoustic cue against noise we supplement the sound localization with a source detection stage. Also, we include a simple onset detector to retain fast response times. Since we only use two microphones, we are confronted with ambiguities on whether a source is in front or behind the device. We resolve these ambiguities with the help of face detection and additional moves. We tailor the system to our target scenarios in experiments with a four minute scripted conversation. In these experiments we evaluate the influence of different system settings on the responsiveness and accuracy of the device.
Pure analytical or experimental methods can only find a control strategy for technical systems with a fixed setup. In former contributions we presented an approach that simultaneously finds the optimal topology and the optimal open-loop control of a system via Mixed Integer Linear Programming (MILP). In order to extend this approach by a closed-loop control we present a Mixed Integer Program for a time discretized tank level control. This model is the basis for an extension by combinatorial decisions and thus for the variation of the network topology. Furthermore, one is able to appraise feasible solutions using the global optimality gap.
Cyber-physical systems are ever more common in manufacturing industries. Increasing their autonomy has been declared an explicit goal, for example, as part of the Industry 4.0 vision. To achieve this system intelligence, principled and software-driven methods are required to analyze sensing data, make goal-directed decisions, and eventually execute and monitor chosen tasks. In this chapter, we present a number of knowledge-based approaches to these problems and case studies with in-depth evaluation results of several different implementations for groups of autonomous mobile robots performing in-house logistics in a smart factory. We focus on knowledge-based systems because besides providing expressive languages and capable reasoning techniques, they also allow for explaining how a particular sequence of actions came about, for example, in the case of a failure.
In the future, we expect manufacturing companies to follow a new paradigm that mandates more automation and autonomy in production processes. Such smart factories will offer a variety of production technologies as services that can be combined ad hoc to produce a large number of different product types and variants cost-effectively even in small lot sizes. This is enabled by cyber-physical systems that feature flexible automated planning methods for production scheduling, execution control, and in-factory logistics.
During development, testbeds are required to determine the applicability of integrated systems in such scenarios. Furthermore, benchmarks are needed to quantify and compare system performance in these industry-inspired scenarios at a comprehensible and manageable size which is, at the same time, complex enough to yield meaningful results.
In this chapter, based on our experience in the RoboCup Logistics League (RCLL) as a specific example, we derive a generic blueprint for how a holistic benchmark can be developed, which combines a specific scenario with a set of key performance indicators as metrics to evaluate the overall integrated system and its components.
Gearboxes are mechanical transmission systems that provide speed and torque conversions from a rotating power source. Being a central element of the drive train, they are relevant for the efficiency and durability of motor vehicles. In this work, we present a new approach for gearbox design: Modeling the design problem as a mixed-integer nonlinear program (MINLP) allows us to create gearbox designs from scratch for arbitrary requirements and—given enough time—to compute provably globally optimal designs for a given objective. We show how different degrees of freedom influence the runtime and present an exemplary solution.
Around 60% of the paper worldwide is made from recovered paper. Especially adhesive contaminants, so called stickies, reduce paper quality. To remove stickies but at the same time keep as many valuable fibers as possible, multi-stage screening systems with several interconnected pressure screens are used. When planning such systems, suitable screens have to be selected and their interconnection as well as operational parameters have to be defined considering multiple conflicting objectives. In this contribution, we present a Mixed-Integer Nonlinear Program to optimize system layout, component selection and operation to find a suitable trade-off between output quality and yield.
Highly competitive markets paired with tremendous production volumes demand particularly cost efficient products. The usage of common parts and modules across product families can potentially reduce production costs. Yet, increasing commonality typically results in overdesign of individual products. Multi domain virtual prototyping enables designers to evaluate costs and technical feasibility of different single product designs at reasonable computational effort in early design phases. However, savings by platform commonality are hard to quantify and require detailed knowledge of e.g. the production process and the supply chain. Therefore, we present and evaluate a multi-objective metamodel-based optimization algorithm which enables designers to explore the trade-off between high commonality and cost optimal design of single products.
The energy-efficiency of technical systems can be improved by a systematic design approach. Technical Operations Research (TOR) employs methods known from Operations Research to find a global optimal layout and operation strategy of technical systems. We show the practical usage of this approach by the systematic design of a decentralized water supply system for skyscrapers. All possible network options and operation strategies are modeled by a Mixed-Integer Nonlinear Program. We present the optimal system found by our approach and highlight the energy savings compared to a conventional system design.