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In this paper we investigate the use of deep neural networks for 3D object detection in uncommon, unstructured environments such as in an open-pit mine. While neural nets are frequently used for object detection in regular autonomous driving applications, more unusual driving scenarios aside street traffic pose additional challenges. For one, the collection of appropriate data sets to train the networks is an issue. For another, testing the performance of trained networks often requires tailored integration with the particular domain as well. While there exist different solutions for these problems in regular autonomous driving, there are only very few approaches that work for special domains just as well. We address both the challenges above in this work. First, we discuss two possible ways of acquiring data for training and evaluation. That is, we evaluate a semi-automated annotation of recorded LIDAR data and we examine synthetic data generation. Using these datasets we train and test different deep neural network for the task of object detection. Second, we propose a possible integration of a ROS2 detector module for an autonomous driving platform. Finally, we present the performance of three state-of-the-art deep neural networks in the domain of 3D object detection on a synthetic dataset and a smaller one containing a characteristic object from an open-pit mine.
In product development, numerous design decisions have to be made. Multi-domain virtual prototyping provides a variety of tools to assess technical feasibility of design options, however often requires substantial computational effort for just a single evaluation. A special challenge is therefore the optimal design of product families, which consist of a group of products derived from a common platform. Finding an optimal platform configuration (stating what is shared and what is individually designed for each product) and an optimal design of all products simultaneously leads to a mixed-integer nonlinear black-box optimization model. We present an optimization approach based on metamodels and a metaheuristic. To increase computational efficiency and solution quality, we compare different types of Gaussian process regression metamodels adapted from the domain of machine learning, and combine them with a genetic algorithm. We illustrate our approach on the example of a product family of electrical drives, and investigate the trade-off between solution quality and computational overhead.
After a brief introduction of conventional laboratory structures, this work focuses on an innovative and universal approach for a setup of a training laboratory for electric machines and drive systems. The novel approach employs a central 48 V DC bus, which forms the backbone of the structure. Several sets of DC machine, asynchronous machine and synchronous machine are connected to this bus. The advantages of the novel system structure are manifold, both from a didactic and a technical point of view: Student groups can work on their own performance level in a highly parallelized and at the same time individualized way. Additional training setups (similar or different) can easily be added. Only the total power dissipation has to be provided, i.e. the DC bus balances the power flow between the student groups. Comparative results of course evaluations of several cohorts of students are shown.
Logic-based robot control in highly dynamic domains / Ferrein, Alexander ; Lakemeyer, Gerhard
(2008)
Objective
In local SAR compression algorithms, the overestimation is generally not linearly dependent on actual local SAR. This can lead to large relative overestimation at low actual SAR values, unnecessarily constraining transmit array performance.
Method
Two strategies are proposed to reduce maximum relative overestimation for a given number of VOPs. The first strategy uses an overestimation matrix that roughly approximates actual local SAR; the second strategy uses a small set of pre-calculated VOPs as the overestimation term for the compression.
Result
Comparison with a previous method shows that for a given maximum relative overestimation the number of VOPs can be reduced by around 20% at the cost of a higher absolute overestimation at high actual local SAR values.
Conclusion
The proposed strategies outperform a previously published strategy and can improve the SAR compression where maximum relative overestimation constrains the performance of parallel transmission.
Intelligent autonomous software robots replacing human activities and performing administrative processes are reality in today’s corporate world. This includes, for example, decisions about invoice payments, identification of customers for a marketing campaign, and answering customer complaints. What happens if such a software robot causes a damage? Due to the complete absence of human activities, the question is not trivial. It could even happen that no one is liable for a damage towards a third party, which could create an uncalculatable legal risk for business partners. Furthermore, the implementation and operation of those software robots involves various stakeholders, which result in the unsolvable endeavor of identifying the originator of a damage. Overall it is advisable to all involved parties to carefully consider the legal situation. This chapter discusses the liability of software robots from an interdisciplinary perspective. Based on different technical scenarios the legal aspects of liability are discussed.
Cardiac MR (CMR) is of proven clinical value but also an area of vigorous ongoing research since image quality is not always exclusively defined by signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Recent developments of CMR at 7.0 T have been driven by pioneering explorations into novel multichannel transmit and receive coil array technology to tackle the challenges B1+-field inhomogeneities, to offset specific-absorption rate (SAR) constraints and to reduce banding artifacts in SSFP imaging. For this study, recognition of the benefits and performance of local surface Tx/Rx-array structures recently established at 7.0 T inspired migration to 3.0 T, where RF inhomogeneities and SAR limitations encountered in routine clinical CMR, though somewhat reduced versus the 7.0 T situation, remain significant. For all these reasons, this study was designed to build and examine the feasibility of a local four channel Tx/Rx cardiac coil array for anatomical and functional cardiac imaging at 3.0 T. For comparison, a homebuilt 4 channel Rx cardiac coil array exhibiting the same geometry as the Tx/Rx coil and a Rx surface coil array were used.
The main objective of our ROS Summer School series is to introduce MA level students to program mobile robots with the Robot Operating System (ROS). ROS is a robot middleware that is used my many research institutions world-wide. Therefore, many state-of-the-art algorithms of mobile robotics are available in ROS and can be deployed very easily. As a basic robot platform we deploy a 1/10 RC cart that is wquipped with an Arduino micro-controller to control the servo motors, and an embedded PC that runs ROS. In two weeks, participants get to learn the basics of mobile robotics hands-on. We describe our teaching concepts and our curriculum and report on the learning success of our students.
K3 User Guide
(2000)
RGB-D sensors such as the Microsoft Kinect or the Asus Xtion are inexpensive 3D sensors. A depth image is computed by calculating the distortion of a known infrared light (IR) pattern which is projected into the scene. While these sensors are great devices they have some limitations. The distance they can measure is limited and they suffer from reflection problems on transparent, shiny, or very matte and absorbing objects. If more than one RGB-D camera is used the IR patterns interfere with each other. This results in a massive loss of depth information. In this paper, we present a simple and powerful method to overcome these problems. We propose a stereo RGB-D camera system which uses the pros of RGB-D cameras and combine them with the pros of stereo camera systems. The idea is to utilize the IR images of each two sensors as a stereo pair to generate a depth map. The IR patterns emitted by IR projectors are exploited here to enhance the dense stereo matching even if the observed objects or surfaces are texture-less or transparent. The resulting disparity map is then fused with the depth map offered by the RGB-D sensor to fill the regions and the holes that appear because of interference, or due to transparent or reflective objects. Our results show that the density of depth information is increased especially for transparent, shiny or matte objects.
Control mechanisms like Industrial Controls Systems (ICS) and its subgroup SCADA (Supervisory Control and Data Acquisition) are a prerequisite to automate industrial processes. While protection of ICS on process management level is relatively straightforward – well known office IT security mechanisms can be used – protection on field bus level is harder to achieve as there are real-time and production requirements like 24x7 to consider. One option to improve security on field bus level is to introduce controls that help to detect and to react on attacks. This paper introduces an initial set of intrusion detection mechanisms for the field bus protocol EtherCAT. To this end existing Ethernet attack vectors including packet injection and man-in-the-middle attacks are tested in an EtherCAT environment, where they could interrupt the EtherCAT network and may even cause physical damage. Based on the signatures of such attacks, a preprocessor and new rule options are defined for the open source intrusion detection system Snort demonstrating the general feasibility of intrusion detection on field bus level.
The adoption of the Digital Health Transformation is a tremendous paradigm change in health organizations, which is not a trivial process in reality. For that reason, in this chapter, it is proposed a methodology with the objective to generate a changing culture in healthcare organisations. Such a change culture is essential for the successful implementation of any supporting methods like Interactive Process Mining. It needs to incorporate (mostly) new ways of team-based and evidence-based approaches for solving structural problems in a digital healthcare environment.
In addition to the technical content, modern courses at university should also teach professional skills to enhance the competencies of students towards their future work. The competency driven approach including technical as well as professional skills makes it necessary to find a suitable way for the integration into the corresponding module in a scalable and flexible manner. Agile development, for example, is essential for the development of modern systems and applications and makes use of dedicated professional skills of the team members, like structured group dynamics and communication, to enable the fast and reliable development. This paper presents an easy to integrate and flexible approach to integrate Scrum, an agile development method, into the lab of an existing module. Due to the different role models of Scrum the students have an individual learning success, gain valuable insight into modern system development and strengthen their communication and organization skills. The approach is implemented and evaluated in the module Vehicle Systems, but it can be transferred easily to other technical courses as well. The evaluation of the implementation considers feedback of all stakeholders, students, supervisor and lecturers, and monitors the observations during project lifetime.
The field of Cognitive Robotics aims at intelligent decision making of autonomous robots. It has matured over the last 25 or so years quite a bit. That is, a number of high-level control languages and architectures have emerged from the field. One concern in this regard is the action language GOLOG. GOLOG has been used in a rather large number of applications as a high-level control language ranging from intelligent service robots to soccer robots. For the lower level robot software, the Robot Operating System (ROS) has been around for more than a decade now and it has developed into the standard middleware for robot applications. ROS provides a large number of packages for standard tasks in robotics like localisation, navigation, and object recognition. Interestingly enough, only little work within ROS has gone into the high-level control of robots. In this paper, we describe our approach to marry the GOLOG action language with ROS. In particular, we present our architecture on inte grating golog++, which is based on the GOLOG dialect Readylog, with the Robot Operating System. With an example application on the Pepper service robot, we show how primitive actions can be easily mapped to the ROS ActionLib framework and present our control architecture in detail.
Information Channels
(2000)
Information and communication technology for integrated mobility concepts such as E-carsharing
(2015)
During the past decade attitude towards sharing things has changed extremely. Not just personal data is shared (e.g. in social networks) but also mobility. Together with the increased ecological awareness of the recent years, new mobility concepts have evolved. E-carsharing has become a symbol for these changes of attitude. The management of a shared car fleet, the energy management of electric mobility and the management of various carsharing users with individual likes and dislikes are just some of the major challenges of e-carsharing. Weaving it into integrated mobility concepts, this raises complexity even further. These challenges can only be overcome by an appropriate amount of well-shaped information available at the right place and time. In order to gather, process and share the required information, fleet cars have to be equipped with modern information and communication technology (ICT) and become so-called fully connected cars. Ensuring the usability of these ICT systems is another challenge that is often neglected, even though it is usability that makes carsharing comfortable, attractive and supports users’ new attitudes. By means of an integrated and consistent concept for human-machine interaction (HMI), the usability of such systems can be raised tremendously.
Recently, novel AI-based services have emerged in the consumer market. AI-based services can affect the way consumers take commercial decisions. Research on the influence of AI on commercial interactions is in its infancy. In this chapter, a framework creating a first overview of the influence of AI on commercial interactions is introduced. This framework summarizes the findings of comparing numerous customer journeys of novel AI-based services with corresponding non-AI equivalents.
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.
31P MR spectroscopic imaging of the human prostate provides information about phosphorylated metabolites that could be used for prostate cancer characterization. The sensitivity of a magnetic field strength of 7 T might enable 3D 31P MR spectroscopic imaging with relevant spatial resolution in a clinically acceptable measurement time. To this end, a 31P endorectal coil was developed and combined with an eight-channel 1H body-array coil to relate metabolic information to anatomical location. An extensive safety validation was performed to evaluate the specific absorption rate, the radiofrequency field distribution, and the temperature distribution of both coils. This validation consisted of detailed Finite Integration Technique simulations, confirmed by MR thermometry and Burn:x-wiley:07403194:media:MRM24175:tex2gif-stack-1 measurements in a phantom and in vivo temperature measurements. The safety studies demonstrated that the presence of the 31P endorectal coil had no influence on the specific absorption rate levels and temperature distribution of the external eight-channel 1H array coil. To stay within a 10 g averaged local specific absorption rate of 10 W/kg, a maximum time-averaged input power of 33 W for the 1H array coil was allowed. For transmitting with the 31P endorectal coil, our safety limit of less than 1°C temperature increase in vivo during a 15-min MR spectroscopic imaging experiment was reached at a time-averaged input power of 1.9 W. With this power setting, a second in vivo measurement was performed on a healthy volunteer. Using adiabatic excitation, 3D 31P MR spectroscopic imaging produced spectra from the entire prostate in 18 min with a spatial resolution of 4 cm3. The spectral resolution enabled the separate detection of phosphocholine, phosphoethanolamine, inorganic phosphate, and other metabolites that could play an important role in the characterization of prostate cancer.
The chemical industry is one of the most important industrial sectors in Germany in terms of manufacturing revenue. While thermodynamic boundary conditions often restrict the scope for reducing the energy consumption of core processes, secondary processes such as cooling offer scope for energy optimisation. In this contribution, we therefore model and optimise an existing cooling system. The technical boundary conditions of the model are provided by the operators, the German chemical company BASF SE. In order to systematically evaluate different degrees of freedom in topology and operation, we formulate and solve a Mixed-Integer Nonlinear Program (MINLP), and compare our optimisation results with the existing system.
In current clinical cardiovascular MR (CMR) practice cardiac motion is commonly dealt with using ECG based synchronization. However, ECG is corrupted by magneto-hydrodynamic (MHD) effects in magnetic fields. This leads to artifacts in the ECG trace and evokes severe T-wave elevations, which might be misinterpreted as R-waves resulting in erroneous triggering. At (ultra)high field strengths, the propensity of ECG recordings to MHD effects is further pronounced. Pulse oximetry (POX) being inherently sensitive to blood oxygenation provides an alternative approach for cardiac gating. However, due to the travel time of the blood the peak of maximum oxygenation and hence the trigger is delayed by approx. 300 ms with respect to the ECG's R-wave. Also the peak of maximum oxygenation shows a jitter of up to 65 ms. Alternative triggering approaches include acoustic cardiac triggering (ACT). In current clinical practice cardiac gating / triggering commonly relies on using single physiological signals only. Realizing this limitation this study proposes a combined triggering approach which exploits multiple physiological signals including ECG, POX or ACT to track cardiac activity. The feasibility of the coupled approach is examined for LV function assessment at 7.0 T. For this purpose, breath-held 2D-CINE imaging in conjunction with cardiac synchronization was performed paralleled by real time logging of physiological waveforms to track (mis)synchronization between the cardiac cycle and data acquisition. Combinations of the ECG, POX and ACT signals were evaluated and processed in real time to facilitate reliable trigger information.
The initial idea of Robotic Process Automation (RPA) is the automation of business processes through the presentation layer of existing application systems. For this simple emulation of user input and output by software robots, no changes of the systems and architecture is required. However, considering strategic aspects of aligning business and technology on an enterprise level as well as the growing capabilities of RPA driven by artificial intelligence, interrelations between RPA and Enterprise Architecture (EA) become visible and pose new questions. In this paper we discuss the relationship between RPA and EA in terms of perspectives and implications. As workin- progress we focus on identifying new questions and research opportunities related to RPA and EA.
Objectives
To assess the image quality of T2-weighted (T2w) magnetic resonance imaging of the prostate and the visibility of prostate cancer at 7 Tesla (T).
Materials & methods
Seventeen prostate cancer patients underwent T2w imaging at 7T with only an external transmit/receive array coil. Three radiologists independently scored images for image quality, visibility of anatomical structures, and presence of artefacts. Krippendorff’s alpha and weighted kappa statistics were used to assess inter-observer agreement. Visibility of prostate cancer lesions was assessed by directly linking the T2w images to the confirmed location of prostate cancer on histopathology.
Results
T2w imaging at 7T was achievable with ‘satisfactory’ (3/5) to ‘good’ (4/5) quality. Visibility of anatomical structures was predominantly scored as ‘satisfactory’ (3/5) and ‘good’ (4/5). If artefacts were present, they were mostly motion artefacts and, to a lesser extent, aliasing artefacts and noise. Krippendorff’s analysis revealed an α = 0.44 between three readers for the overall image quality scores. Clinically significant cancer lesions in both peripheral zone and transition zone were visible at 7T.
Conclusion
T2w imaging with satisfactory to good quality can be routinely acquired, and cancer lesions were visible in patients with prostate cancer at 7T using only an external transmit/receive body array coil.
Hybrid control for autonomous systems — Integrating learning, deliberation and reactive control
(2010)
How does the implementation of a next generation network influence a telecommunication company?
(2009)
As the potential of a Next Generation Network (NGN) is recognized, telecommunication companies consider switching to it. Although the implementation of an NGN seems to be merely a modification of the network infrastructure, it may trigger or require changes in the whole company and even influence the company strategy. To capture the effects of NGN we propose a framework based on concepts of business engineering and technical recommendations for the introduction of NGN technology. The specific design of solutions for the layers "Strategy", "Processes" and "Information Systems" as well as their interdependencies are an essential characteristic of the developed framework. We have per-formed a case study on NGN implementation and observed that all layers captured by our framework are influenced by the introduction of an NGN.
his report summarizes the results of a workshop on Groupware related task design which took place at the International Conference on Supporting Group Work Group'99, Arizona, from 14 th to 17 th November 1999.
The workshop was addressed to people from different
viewpoints, backgrounds, and domains:
- Researchers dealing with questions of task analysis
and task modeling for Groupware application from an
academic point of view. They may contribute modelbased design
approaches or theoretically oriented
work
- Practitioners with experience in the design and
everyday use of groupware systems. They might refer
to the practical side of the topic: "real" tasks, "real"
problems, "real" users, etc.
Water suppliers are faced with the great challenge of achieving high-quality and, at the same time, low-cost water supply. In practice, the focus is set on the most beneficial maintenance measures and/or capacity adaptations of existing water distribution systems (WDS). Since climatic and demographic influences will pose further challenges in the future, the resilience enhancement of WDS, i.e. the enhancement of their capability to withstand and recover from disturbances, has been in particular focus recently. To assess the resilience of WDS, metrics based on graph theory have been proposed. In this study, a promising approach is applied to assess the resilience of the WDS for a district in a major German City. The conducted analysis provides insight into the process of actively influencing the
resilience of WDS
Grain boundary and surface segragation of Ba-Ti-O-Phases in rutile. O´Bryan, H. M.; Hagemann, H. J.
(1987)
One central challenge for self-driving cars is a proper path-planning. Once a trajectory has been found, the next challenge is to accurately and safely follow the precalculated path. The model-predictive controller (MPC) is a common approach for the lateral control of autonomous vehicles. The MPC uses a vehicle dynamics model to predict the future states of the vehicle for a given prediction horizon. However, in order to achieve real-time path control, the computational load is usually large, which leads to short prediction horizons. To deal with the computational load, the control algorithm can be parallelized on the graphics processing unit (GPU). In contrast to the widely used stochastic methods, in this paper we propose a deterministic approach based on grid search. Our approach focuses on systematically discovering the search area with different levels of granularity. To achieve this, we split the optimization algorithm into multiple iterations. The best sequence of each iteration is then used as an initial solution to the next iteration. The granularity increases, resulting in smooth and predictable steering angle sequences. We present a novel GPU-based algorithm and show its accuracy and realtime abilities with a number of real-world experiments.
To train end users how to interact with digital systems is indispensable to ensure a strong computer security. 'Competence Developing Game'-based approaches are particularly suitable for this purpose because of their motivation-and simulation-aspects. In this paper the Competence Developing Game 'GHOST' for cybersecurity awareness trainings and its underlying patterns are described. Accordingly, requirements for an 'Competence Developing Game' based training are discussed. Based on these requirements it is shown how a game can fulfill these requirements. A supplementary game interaction design and a corresponding evaluation study is shown. The combination of training requirements and interaction design is used to create a 'Competence Developing Game'-based training concept. A part of these concept is implemented into a playable prototype that serves around one hour of play respectively training time. This prototype is used to perform an evaluation of the game and training aspects of the awareness training. Thereby, the quality of the game aspect and the effectiveness of the training aspect are shown.
In the RoboCup@Home domestic service robot competition, complex tasks such as "get the cup from the kitchen and bring it to the living room" or "find me this and that object in the apartment" have to be accomplished. At these competitions the robots may only be instructed by natural language. As humans use qualitative concepts such as "near" or "far", the robot needs to cope with them, too. For our domestic robot, we use the robot programming and plan language Readylog, our variant of Golog. In previous work we extended the action language Golog, which was developed for the high-level control of agents and robots, with fuzzy concepts and showed how to embed fuzzy controllers in Golog. In this paper, we demonstrate how these notions can be fruitfully applied to two domestic service robotic scenarios. In the first application, we demonstrate how qualitative fluents based on a fuzzy set semantics can be deployed. In the second program, we show an example of a fuzzy controller for a follow-a-person task.