TY - RPRT A1 - Auer, Veronika A1 - Beneken, Gerd A1 - Brummer, Benjamin A1 - Châteauvieux-Hellwig, Camille A1 - Engler, Benjamin A1 - Gilly, Alexander A1 - Hagl, Rainer A1 - Hummel, Felix A1 - Hummel, Sabine A1 - Karlinger, Peter A1 - Knorr, Ludwig A1 - Köster, Heinrich A1 - Kucich, Martin A1 - Mecking, Simon A1 - Rabold, Andreas A1 - Sandor, Viktor A1 - Schalk, Daniel A1 - Schanda, Ulrich A1 - Schemme, Michael A1 - Schiffner, Ivonne A1 - Schmidt, Jochen A1 - Schugmann, Reinhard A1 - Seidlmeier, Heinrich A1 - Sigg, Ferdinand A1 - Stauss, Kilian A1 - Sussmann, Monika A1 - Wellisch, Ulrich A1 - Wenninger, Marc A1 - Wittmann, Josef A1 - Zscheile, Matthias T1 - Jahresbericht 2016, Forschung - Entwicklung - Innovation N2 - Mit dem jährlich erscheinenden Forschungsbericht möchte die Hochschule Rosenheim einen Einblick in ihre vielfältigen Projekte und Aktivitäten der angewandten Forschung und Entwicklung geben. Im Jahresbericht 2016 wird über Vorhaben im Jahr 2016 berichtet. T3 - Schriftenreihen - Forschungsbericht - 5 KW - Forschung Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:861-opus4-12282 ER - TY - RPRT A1 - Ackermann, Timo A1 - Angermeier, Martin A1 - Auer, Veronika A1 - Beneken, Gerd A1 - Bernhardt, Andreas A1 - Botsch, Rafael A1 - Bücker, Dominikus A1 - Hager, Ralf A1 - Hauck-Bauer, Eva A1 - Heigl, Martin A1 - Hirschmüller, Sebastian A1 - Höllmüller, Janett A1 - Karlinger, Peter A1 - Köster, Heinrich A1 - Krause, Harald A1 - Kucich, Martin A1 - Matthias, Kira A1 - Patzl, Victoria A1 - Plönnigs, René A1 - Posch, Georg A1 - Schanda, Ulrich A1 - Scheerer, Josua A1 - Schlecht, Johannes A1 - Schmidt, Jochen A1 - Stichler, Markus A1 - Uhl, Cornelius A1 - Viehhauser, Peter A1 - Weber, Gabriel A1 - Wolf, Christopher A1 - Zagler, Stefan A1 - Zentgraf, Peter T1 - Forschungsbericht 2013 N2 - Mit dem jährlich erscheinenden Forschungsbericht möchte die Hochschule Rosenheim einen Einblick in ihre vielfältigen Projekte und Aktivitäten der angewandten Forschung und Entwicklung geben. Im Forschungsbericht 2013 wird über Vorhaben im Jahr 2013 berichtet. T3 - Schriftenreihen - Forschungsbericht - 2 KW - Forschung Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:861-opus4-12324 ER - TY - JOUR A1 - Wenninger, Marc A1 - Bayerl, Sebastian P. A1 - Schmidt, Jochen A1 - Riedhammer, Korbinian T1 - Timage – A Robust Time Series Classification Pipeline JF - Artificial Neural Networks and Machine Learning – ICANN 2019: Text and Time Series. ICANN 2019. Lecture Notes in Computer Science N2 - Time series are series of values ordered by time. This kind of data can be found in many real world settings. Classifying time series is a difficult task and an active area of research. This paper investigates the use of transfer learning in Deep Neural Networks and a 2D representation of time series known as Recurrence Plots. In order to utilize the research done in the area of image classification, where Deep Neural Networks have achieved very good results, we use a Residual Neural Networks architecture known as ResNet. As preprocessing of time series is a major part of every time series classification pipeline, the method proposed simplifies this step and requires only few parameters. For the first time we propose a method for multi time series classification: Training a single network to classify all datasets in the archive with one network. We are among the first to evaluate the method on the latest 2018 release of the UCR archive, a well established time series classification benchmarking dataset. KW - neural networks Y1 - 2019 VL - 11730 PB - Springer CY - Cham ER - TY - JOUR A1 - Wenninger, Marc A1 - Stecher, Dominik A1 - Schmidt, Jochen T1 - SVM-Based Segmentation of Home Appliance Energy Measurements JF - Proceedings 8th IEEE International Conference on Machine Learning and Applications -ICMLA 2019 N2 - Generating a more detailed understanding of domestic electricity demand is a major topic for energy suppliers and householders in times of climate change. Over the years there have been many studies on consumption feedback systems to inform householders, disaggregation algorithms for Non-Intrusive-Load-Monitoring (NILM), Real-Time-Pricing (RTP) to promote supply aware behavior through monetary incentives and appliance usage prediction algorithms. While these studies are vital steps towards energy awareness, one of the most fundamental challenges has not yet been tackled: Automated detection of start and stop of usage cycles of household appliances. We argue that most research efforts in this area will benefit from a reliable segmentation method to provide accurate usage information. We propose a SVM-based segmentation method for home appliances such as dishwashers and washing machines. The method is evaluated using manually annotated electricity measurements of five different appliances recorded over two years in multiple households. KW - Machine Learning Y1 - 2019 SP - 1666 EP - 1670 ER - TY - BOOK A1 - Schmidt, Jochen T1 - Grundkurs Informatik - Das Übungsbuch: 148 Aufgaben mit Lösungen KW - Grundlagen Übungen Y1 - 2019 SN - 978-3658259440 PB - Springer Vieweg CY - Wiesbaden ET - 1 ER - TY - BOOK A1 - Beneken, Gerd A1 - Ernst, H. A1 - Schmidt, Jochen T1 - Grundkurs Informatik: Grundlagen und Konzepte für die erfolgreiche IT-Praxis - Eine umfassende, praxisorientierte Einführung (Auflage von 2015) N2 - Das Buch bietet eine umfassende und praxisorientierte Einführung in die wesentlichen Grundlagen und Konzepte der Informatik. Es umfasst den Stoff, der typischerweise in den ersten Semestern eines Informatikstudiums vermittelt wird, vertieft Zusammenhänge, die darüber hinausgehen und macht sie verständlich. Die Themenauswahl orientiert sich an der langfristigen Relevanz für die praktische Anwendung. Praxisnah und aktuell werden die Inhalte für Studierende der Informatik und verwandter Studiengänge sowie für im Beruf stehende Praktiker vermittelt. Die vorliegende fünfte Auflage wurde grundlegend überarbeitet und aktualisiert. KW - Informatik KW - Lehrbuch KW - IT- Praxis Y1 - 2015 PB - Springer Vieweg CY - Berlin ER - TY - CHAP A1 - Wenninger, Marc A1 - Schmidt, Jochen A1 - Goeller, Toni T1 - Appliance Usage Prediction for the Smart Home with an Application to Energy Demand Side Management - And Why Accuracy is not a Good Performance Metric for this Problem. T2 - 6th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS) N2 - Shifting energy peak load is a subject that plays a huge role in the currently changing energy market, where renewable energy sources no longer produce the exact amount of energy demanded. Matching demand to supply requires behavior Changes on the customerside, which can be achieved by incentives suchas Real-Time-Pricing (RTP). Various studies show that such incentives cannot be utilized without a complexity reduction, e.g., by smart home automation systems that inform the customer about possible savings or automatically schedule appliances to off-peak load phases. We propose a probabilistic appliance usage prediction based on historical energy data that can be used to identify the times of day where an appliance will be used and therefore make load shift recommendations that suite the customer’s usage profile. A huge issue is how to provide a valid performance evaluation for this particular problem. We will argue why the commonly used accuracy metric is not suitable, and suggest to use other metrics like the area under the Receiver Operating Characteristic (ROC) curve, Matthews Correlation Coefficient (MCC) or F1-Score instead. KW - Real Time Pricing (RTP) KW - Household Appliance Usage Prediction KW - Demand Side Management Y1 - 2017 ER - TY - CHAP A1 - Goeller, Toni A1 - Wenninger, Marc A1 - Schmidt, Jochen T1 - Towards Cost-Effective Utility Business Models - Selecting a Communication Architecture for the Rollout of New Smart Energy Services T2 - Proceedings of the 7th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS N2 - The IT architecture for meter reading and utility services is at the core of new business models and has a decisive role as an enabler for resource efficiency measures. The communication architecture used by those services has significant impact on cost, flexibility and speed of new service rollout. This article describes how the dominant system model for meter reading came about, what alternative models exist, and what trade-offs those models have for rollout of new services by different stakeholders. Control of a self learning home automation system by dynamic tariff information (Real-Time-Pricing) is given as an application example. KW - Smart Meter, Advanced Metering Infrastructure, AMI Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:861-opus4-8332 SN - 978-989-758-292-9 SP - 231 EP - 237 PB - SciTePress ER - TY - BOOK A1 - Ernst, H. A1 - Schmidt, Jochen A1 - Beneken, Gerd T1 - Grundkurs Informatik: Grundlagen und Konzepte für die erfolgreiche IT-Praxis - Eine umfassende, praxisorientierte Einführung N2 - Zahlensysteme und binäre Arithmetik Nachricht und Information Codierung und Datenkompression Verschlüsselung Schaltalgebra, Schaltnetze und Elemente der Computerhardware Rechnerarchitekturen Rechnernetze Betriebssysteme Datenbanken Automatentheorie und formale Sprachen Berechenbarkeit und Komplexität Suchen und Sortieren Bäume und Graphen prozedurale und objektorientierte Programmierung (C und Java) Anwendungsprogrammierung im Internet (HTML, CSS, JavaScript und PHP) Software-Engineering KW - Informatik KW - Anwendungsprogrammierung im Internet Y1 - 2016 PB - Springer Vieweg CY - Berlin ER - TY - CHAP A1 - Zenger, A. A1 - Schmidt, Jochen A1 - Krödel, M. T1 - Towards the Intelligent Home: Using Reinforcement-Learning for Optimal Heating Control T2 - Advances in Artificial Intelligence, Proceedings of the 36th Annual Conference on AI, volume 8077 of Lecture Notes in Artificial Intelligence N2 - We propose a reinforcement learning approach to heating control in home automation, that can acquire a set of rules enabling an agent to heat a room to the desired temperature at a defined time while conserving as much energy as possible. Experimental results are presented that show the feasibility of our method. KW - Target Temperature KW - Reward Function KW - Heating control KW - Home Automation KW - Approximate dynamic program Y1 - 2013 PB - Springer ER - TY - JOUR A1 - Darms, M. A1 - Fölster, F. A1 - Schmidt, Jochen A1 - Fröhlich, D. A1 - Eckert, A. T1 - Data Fusion Strategies in Advanced Driver Assistance Systems JF - SAE International Journal of Passenger Cars – Electronic and Electrical Systems N2 - Data fusion plays a central role in more and more automotive applications, especially for driver assistance systems. On the one hand the process of data fusion combines data and information to estimate or predict states of observed objects. On the other hand data fusion introduces abstraction layers for data description and allows building more flexible and modular systems.The data fusion process can be divided into a low-level processing (tracking and object discrimination) and a high level processing (situation assessment). High level processing becomes more and more the focus of current research as different assistance applications will be combined into one comprehensive assistance system. Different levels/strategies for data fusion can be distinguished: Fusion on raw data level, fusion on feature level and fusion on decision level. All fusion strategies can be found in current driver assistance implementations. The paper gives an overview of the different fusion strategies and shows their application in current driver assistance systems. For low level processing a raw data fusion approach in a stereo video system is described, as an example for feature level fusion the fusion of radar and camera data for tracking is explained. As an example for a high level fusion algorithm an approach for a situation assessment based on multiple sensors is given. The paper describes practical realizations of these examples and points out their potential to further increase traffic safety with reasonably low cost for the overall system. KW - Driver Assistent Systems KW - Data Fusion KW - automotive applications Y1 - 2010 ER - TY - CHAP A1 - Wong, C.K. A1 - Yeap, W.K. A1 - Schmidt, Jochen T1 - Our Next Generation of Robotics Researchers? Teaching Robotics at Primary School Level. T2 - Readings in Technology and Education: Proceedings of International Conference on Information Communication Technologies in Education N2 - In this paper, we present our experience in designing and teaching of our first robotics course for students at primary school level. The course was carried out over a comparatively short period of time, namely 6 weeks, 2 hours per week. In contrast to many other projects, we use robots that researchers used to conduct their research and discuss problems faced by these researchers. Thus, this is not a behavioural study but a hands-on learning experience for the students. The aim is to highlight the development of autonomous robots and artificial intelligence as well as to promote science and robotics in schools. KW - Robotic Research KW - Teaching Robotics KW - Software Development Y1 - 2009 ER - TY - JOUR A1 - Schmidt, Jochen A1 - Niemann, H. T1 - Data Selection for Hand-eye Calibration: A Vector Quantization Approach JF - The International Journal of Robotics Research N2 - This paper presents new vector quantization based methods for selecting well-suited data for hand-eye calibration from a given sequence of hand and eye movements. Data selection can improve the accuracy of classic hand-eye calibration, and make it possible in the first place in situations where the standard approach of manually selecting positions is inconvenient or even impossible, especially when using continuously recorded data. A variety of methods is proposed, which differ from each other in the dimensionality of the vector quantization compared to the degrees of freedom of the rotation representation, and how the rotation angle is incorporated. The performance of the proposed vector quantization based data selection methods is evaluated using data obtained from a manually moved optical tracking system (hand) and an endoscopic camera (eye). KW - hand- eye calibration KW - vektor quantization Y1 - 2018 ER - TY - CHAP A1 - Yeap, W.K. A1 - Wong, C.K. A1 - Schmidt, Jochen T1 - Using a Mobile Robot to Test a Theory of Cognitive Mapping. T2 - Robotics and Cognitive Approaches to Spatial Mapping, Springer Tracts in Advanced Robotics N2 - This paper describes using a mobile robot, equipped with some sonar sensors and an odometer, to test navigation through the use of a cognitive map. The robot explores an office environment, computes a cognitive map, which is a network of ASRs [36, 35], and attempts to find its way home. Ten trials were conducted and the robot found its way home each time. From four random positions in two trials, the robot estimated the home position relative to its current position reasonably accurately. Our robot does not solve the simultaneous localization and mapping problem and the map computed is fuzzy and inaccurate with much of the details missing. In each homeward journey, it computes a new cognitive map of the same part of the environment, as seen from the perspective of the homeward journey. We show how the robot uses distance information from both maps to find its way home. KW - Cognitive Mapping KW - Mobile Robot KW - Simultaneous Localization  Y1 - 2008 PB - Springer CY - Berlin ER - TY - CHAP A1 - Schmidt, Jochen A1 - Wong, C.K. A1 - Yeap, W.K. T1 - Spatial Information Extraction for Cognitive Mapping with a Mobile Robot. T2 - Conference on Spatial Information Theory: COSIT'07, Melbourne, Australia. Volume 4736 of Lecture Notes in Computer Science N2 - When animals (including humans) first explore a new environment, what they remember is fragmentary knowledge about the places visited. Yet, they have to use such fragmentary knowledge to find their way home. Humans naturally use more powerful heuristics while lower animals have shown to develop a variety of methods that tend to utilize two key pieces of information, namely distance and orientation information. Their methods differ depending on how they sense their environment. Could a mobile robot be used to investigate the nature of such a process, commonly referred to in the psychological literature as cognitive mapping? What might be computed in the initial explorations and how is the resulting “cognitive map” be used for localization? In this paper, we present an approach using a mobile robot to generate a “cognitive map”, the main focus being on experiments conducted in large spaces that the robot cannot apprehend at once due to the very limited range of its sensors. The robot computes a “cognitive map” and uses distance and orientation information for localization. KW - Mobile Robot KW - Sonar Sensor KW - Robotic Research Y1 - 2018 ER - TY - JOUR A1 - Schmidt, Jochen A1 - Wong, C.K. A1 - Yeap, W.K. T1 - Localisation and Mapping with a Mobile Robot Using Sparse Range Data JF - Autonomous Robots and Agents, Studies in Computational Intelligence (SCI), N2 - We present an approach for indoor mapping and localisation using sparse range data, acquired by a mobile robot equipped with sonar sensors. The chapter consists of two main parts. First, a split and merge based method for dividing a given metric map into distinct regions is presented, thus creating a topological map in a metric framework. Spatial information extracted from this map is then used for self-localisation on the return home journey. The robot computes local confidence maps for two simple localisation strategies based on distance and relative orientation of regions. These local maps are then fused to produce overall confidence maps. KW - Mobile Robot KW - Sonar Sensor KW - Sensor Data Fusion KW - Robotic Research Y1 - 2007 PB - Springer ER - TY - CHAP A1 - Wong, C.K. A1 - Yeap, W.K. A1 - Schmidt, Jochen T1 - Using a Mobile Robot for Cognitive Mapping T2 - International Joint Conference on Artificial Intelligence (IJCAI), pages 2243-2248, Hyderabad, India, 2007 N2 - When animals (including humans) first explore a new environment, what they remember is fragmentary knowledge about the places visited. Yet, they have to use such fragmentary knowledge to find their way home. Humans naturally use more powerful heuristics while lower animals have shown to developa varietyof methodsthat tend to utilize two key pieces of information,namely distance and orientation information. Their methods differ depending on how they sense their environment. Could a mobile robot be used to investigate the nature of such a process, commonly referred to in the psychological literature as cognitive mapping? What might be computed in the initial explorations and how is the resulting “cognitive map” be used to return home? In this paper, we presented a novel approach using a mobile robot to do cognitive mapping. Our robot computes a “cognitive map” and uses distance and orientation information to find its way home. The process developed provides interesting insights into the nature of cognitive mapping and encourages us to use a mobile robot to do cognitive mapping in the future, as opposed to its popular use in robot mapping. KW - Cognitive Mapping KW - Sonar Sensor KW - Robotic Research Y1 - 2007 ER - TY - BOOK A1 - Schmidt, Jochen T1 - 3-D Reconstruction and Stereo Self-Calibration for Augmented Reality N2 - The main focus of this work is the development of new methods for the self-calibration of a rigid stereo camera system. However, many of the algorithms introduced here have a wider impact, particularly in robot hand-eye calibration with all its different areas of application. Stereo self-calibration refers to the computation of the intrinsic and extrinsic parameters of a stereo rig using neither a priori knowledge on the movement of the rig nor on the geometry of the observed scene. The stereo parameters obtained by self-calibration, namely rotation and translation from left to right camera, are used for computing depth maps for both images, which are applied for rendering correctly occluded virtual objects into a real scene (Augmented Reality). The proposed methods were evaluated on real and synthetic data and compared to algorithms from the literature. In addition to a stereo rig, an optical tracking system with a camera mounted on an endoscope was calibrated without a calibration pattern using the proposed extended hand-eye calibration algorithm. The self-calibration methods developed in this work have a number of features, which make them easily applicable in practice: They rely on temporal feature tracking only, as this monocular tracking in a continuous image sequence is much easier than left-to-right tracking when the camera parameters are still unknown. Intrinsic and extrinsic camera parameters are computed during the self-calibration process, i.e., no calibration pattern is required. The proposed stereo self-calibration approach can also be used for extended hand-eye calibration, where the eye poses are obtained by structure-from-motion rather than from a calibration pattern. An inherent problem to hand-eye calibration is that it requires at least two general movements of the cameras in order to compute the rigid transformation. If the motion is not general enough, only a part of the parameters can be obtained, which would not be sufficient for computing depth maps. Therefore, a main part of this work discusses methods for data selection that increase the robustness of hand-eye calibration. Different new approaches are shown, the most successful ones being based on vector quantization. The data selection algorithms developed in this work can not only be used for stereo self-calibration, but also for classic robot hand-eye calibration, and they are independent of the actually used hand-eye calibration algorithm. KW - Augmented Reality (AR) KW - Stereo Self-Calibration Y1 - 2018 PB - Logos CY - Berlin ER - TY - CHAP A1 - Zinßer, T. A1 - Schmidt, Jochen A1 - Niemann, H. T1 - Performance Analysis of Nearest Neighbor Algorithms for ICP Registration of 3-D Point Sets T2 - Vision, Modeling, and Visualization 2003 N2 - There are many nearest neighbor algorithms tailor made for ICP,but most of them require Special input data like range Images or triangle meshes. We focus on efficient nearest neighbor algorithms that do not impose this limitation, and thus can also be used with 3-D point sets generated by structure-frommotion techniques. We shortly present the evaluated algorithms and introduce the modifications we made to improve their efficiency. In particular, several enhancements to the well-known k-D tree algorithm are described. The first part of our Performance Analysis consists of Experiments on synthetic point sets, whereas the second part features experiments with the ICP algorithm on real point sets. Both parts are completed by a thorough evaluation of the obtained results. KW - ICP Algorithm KW - 3D Point-Sets Y1 - 2003 ER - TY - JOUR A1 - Zobel, M. A1 - Denzler, J. A1 - Heigl, B. A1 - Nöth, E. A1 - Paulus, D. A1 - Schmidt, Jochen A1 - Stemmer, G. T1 - MOBSY: Integration of vision and dialogue in service robots JF - Machine Vision and Applications N2 - This contribution introduces MOBSY, a fully integrated, autonomous mobile service robot system. It acts as an automatic dialogue-based receptionist for visitors to our institute. MOBSY incorporates many techniques from different research areas into one working stand-alone system. The techniques involved range from computer vision over speech understanding to classical robotics. Along with the two main aspects of vision and speech, we also focus on the integration aspect, both on the methodological and on the technical level. We describe the task and the techniques involved. Finally, we discuss the experiences that we gained with MOBSY during a live performance at our institute. KW - Service robots KW - Computer vision KW - Speech understanding and dialogue KW - Integrated System Y1 - 2003 ER -