@techreport{AuerBenekenBrummeretal.2017, author = {Auer, Veronika and Beneken, Gerd and Brummer, Benjamin and Ch{\^a}teauvieux-Hellwig, Camille and Engler, Benjamin and Gilly, Alexander and Hagl, Rainer and Hummel, Felix and Hummel, Sabine and Karlinger, Peter and Knorr, Ludwig and K{\"o}ster, Heinrich and Kucich, Martin and Mecking, Simon and Rabold, Andreas and Sandor, Viktor and Schalk, Daniel and Schanda, Ulrich and Schemme, Michael and Schiffner, Ivonne and Schmidt, Jochen and Schugmann, Reinhard and Seidlmeier, Heinrich and Sigg, Ferdinand and Stauss, Kilian and Sussmann, Monika and Wellisch, Ulrich and Wenninger, Marc and Wittmann, Josef and Zscheile, Matthias}, title = {Jahresbericht 2016, Forschung - Entwicklung - Innovation}, organization = {Hochschule Rosenheim}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:861-opus4-12282}, pages = {68}, year = {2017}, abstract = {Mit dem j{\"a}hrlich erscheinenden Forschungsbericht m{\"o}chte die Hochschule Rosenheim einen Einblick in ihre vielf{\"a}ltigen Projekte und Aktivit{\"a}ten der angewandten Forschung und Entwicklung geben. Im Jahresbericht 2016 wird {\"u}ber Vorhaben im Jahr 2016 berichtet.}, language = {de} } @techreport{AckermannAngermeierAueretal.2014, author = {Ackermann, Timo and Angermeier, Martin and Auer, Veronika and Beneken, Gerd and Bernhardt, Andreas and Botsch, Rafael and B{\"u}cker, Dominikus and Hager, Ralf and Hauck-Bauer, Eva and Heigl, Martin and Hirschm{\"u}ller, Sebastian and H{\"o}llm{\"u}ller, Janett and Karlinger, Peter and K{\"o}ster, Heinrich and Krause, Harald and Kucich, Martin and Matthias, Kira and Patzl, Victoria and Pl{\"o}nnigs, Ren{\´e} and Posch, Georg and Schanda, Ulrich and Scheerer, Josua and Schlecht, Johannes and Schmidt, Jochen and Stichler, Markus and Uhl, Cornelius and Viehhauser, Peter and Weber, Gabriel and Wolf, Christopher and Zagler, Stefan and Zentgraf, Peter}, title = {Forschungsbericht 2013}, organization = {Hochschule Rosenheim}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:861-opus4-12324}, pages = {56}, year = {2014}, abstract = {Mit dem j{\"a}hrlich erscheinenden Forschungsbericht m{\"o}chte die Hochschule Rosenheim einen Einblick in ihre vielf{\"a}ltigen Projekte und Aktivit{\"a}ten der angewandten Forschung und Entwicklung geben. Im Forschungsbericht 2013 wird {\"u}ber Vorhaben im Jahr 2013 berichtet.}, language = {de} } @article{WenningerBayerlSchmidtetal.2019, author = {Wenninger, Marc and Bayerl, Sebastian P. and Schmidt, Jochen and Riedhammer, Korbinian}, title = {Timage - A Robust Time Series Classification Pipeline}, series = {Artificial Neural Networks and Machine Learning - ICANN 2019: Text and Time Series. ICANN 2019. Lecture Notes in Computer Science}, volume = {11730}, journal = {Artificial Neural Networks and Machine Learning - ICANN 2019: Text and Time Series. ICANN 2019. Lecture Notes in Computer Science}, publisher = {Springer}, address = {Cham}, year = {2019}, abstract = {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.}, language = {en} } @article{WenningerStecherSchmidt2019, author = {Wenninger, Marc and Stecher, Dominik and Schmidt, Jochen}, title = {SVM-Based Segmentation of Home Appliance Energy Measurements}, series = {Proceedings 8th IEEE International Conference on Machine Learning and Applications -ICMLA 2019}, journal = {Proceedings 8th IEEE International Conference on Machine Learning and Applications -ICMLA 2019}, pages = {1666 -- 1670}, year = {2019}, abstract = {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.}, language = {en} } @book{Schmidt2019, author = {Schmidt, Jochen}, title = {Grundkurs Informatik - Das {\"U}bungsbuch: 148 Aufgaben mit L{\"o}sungen}, edition = {1}, publisher = {Springer Vieweg}, address = {Wiesbaden}, isbn = {978-3658259440}, publisher = {Technische Hochschule Rosenheim}, pages = {196}, year = {2019}, language = {de} } @book{BenekenErnstSchmidt2015, author = {Beneken, Gerd and Ernst, H. and Schmidt, Jochen}, title = {Grundkurs Informatik: Grundlagen und Konzepte f{\"u}r die erfolgreiche IT-Praxis - Eine umfassende, praxisorientierte Einf{\"u}hrung (Auflage von 2015)}, publisher = {Springer Vieweg}, address = {Berlin}, publisher = {Technische Hochschule Rosenheim}, year = {2015}, abstract = {Das Buch bietet eine umfassende und praxisorientierte Einf{\"u}hrung in die wesentlichen Grundlagen und Konzepte der Informatik. Es umfasst den Stoff, der typischerweise in den ersten Semestern eines Informatikstudiums vermittelt wird, vertieft Zusammenh{\"a}nge, die dar{\"u}ber hinausgehen und macht sie verst{\"a}ndlich. Die Themenauswahl orientiert sich an der langfristigen Relevanz f{\"u}r die praktische Anwendung. Praxisnah und aktuell werden die Inhalte f{\"u}r Studierende der Informatik und verwandter Studieng{\"a}nge sowie f{\"u}r im Beruf stehende Praktiker vermittelt. Die vorliegende f{\"u}nfte Auflage wurde grundlegend {\"u}berarbeitet und aktualisiert.}, language = {de} } @inproceedings{WenningerSchmidtGoeller2017, author = {Wenninger, Marc and Schmidt, Jochen and Goeller, Toni}, title = {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.}, series = {6th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS)}, booktitle = {6th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS)}, year = {2017}, abstract = {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.}, language = {en} } @inproceedings{GoellerWenningerSchmidt2018, author = {Goeller, Toni and Wenninger, Marc and Schmidt, Jochen}, title = {Towards Cost-Effective Utility Business Models - Selecting a Communication Architecture for the Rollout of New Smart Energy Services}, series = {Proceedings of the 7th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS}, booktitle = {Proceedings of the 7th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS}, publisher = {SciTePress}, isbn = {978-989-758-292-9}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:861-opus4-8332}, pages = {231 -- 237}, year = {2018}, abstract = {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.}, language = {en} } @book{ErnstSchmidtBeneken2016, author = {Ernst, H. and Schmidt, Jochen and Beneken, Gerd}, title = {Grundkurs Informatik: Grundlagen und Konzepte f{\"u}r die erfolgreiche IT-Praxis - Eine umfassende, praxisorientierte Einf{\"u}hrung}, publisher = {Springer Vieweg}, address = {Berlin}, publisher = {Technische Hochschule Rosenheim}, year = {2016}, abstract = {Zahlensysteme und bin{\"a}re Arithmetik Nachricht und Information Codierung und Datenkompression Verschl{\"u}sselung Schaltalgebra, Schaltnetze und Elemente der Computerhardware Rechnerarchitekturen Rechnernetze Betriebssysteme Datenbanken Automatentheorie und formale Sprachen Berechenbarkeit und Komplexit{\"a}t Suchen und Sortieren B{\"a}ume und Graphen prozedurale und objektorientierte Programmierung (C und Java) Anwendungsprogrammierung im Internet (HTML, CSS, JavaScript und PHP) Software-Engineering}, language = {de} } @inproceedings{ZengerSchmidtKroedel2013, author = {Zenger, A. and Schmidt, Jochen and Kr{\"o}del, M.}, title = {Towards the Intelligent Home: Using Reinforcement-Learning for Optimal Heating Control}, series = {Advances in Artificial Intelligence, Proceedings of the 36th Annual Conference on AI, volume 8077 of Lecture Notes in Artificial Intelligence}, booktitle = {Advances in Artificial Intelligence, Proceedings of the 36th Annual Conference on AI, volume 8077 of Lecture Notes in Artificial Intelligence}, publisher = {Springer}, year = {2013}, abstract = {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.}, language = {en} } @article{DarmsFoelsterSchmidtetal.2010, author = {Darms, M. and F{\"o}lster, F. and Schmidt, Jochen and Fr{\"o}hlich, D. and Eckert, A.}, title = {Data Fusion Strategies in Advanced Driver Assistance Systems}, series = {SAE International Journal of Passenger Cars - Electronic and Electrical Systems}, journal = {SAE International Journal of Passenger Cars - Electronic and Electrical Systems}, year = {2010}, abstract = {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.}, language = {en} } @inproceedings{WongYeapSchmidt2009, author = {Wong, C.K. and Yeap, W.K. and Schmidt, Jochen}, title = {Our Next Generation of Robotics Researchers? Teaching Robotics at Primary School Level.}, series = {Readings in Technology and Education: Proceedings of International Conference on Information Communication Technologies in Education}, booktitle = {Readings in Technology and Education: Proceedings of International Conference on Information Communication Technologies in Education}, year = {2009}, abstract = {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.}, language = {de} } @article{SchmidtNiemann2008, author = {Schmidt, Jochen and Niemann, H.}, title = {Data Selection for Hand-eye Calibration: A Vector Quantization Approach}, series = {The International Journal of Robotics Research}, journal = {The International Journal of Robotics Research}, year = {2008}, abstract = {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).}, language = {en} } @incollection{YeapWongSchmidt2008, author = {Yeap, W.K. and Wong, C.K. and Schmidt, Jochen}, title = {Using a Mobile Robot to Test a Theory of Cognitive Mapping.}, series = {Robotics and Cognitive Approaches to Spatial Mapping, Springer Tracts in Advanced Robotics}, booktitle = {Robotics and Cognitive Approaches to Spatial Mapping, Springer Tracts in Advanced Robotics}, publisher = {Springer}, address = {Berlin}, publisher = {Technische Hochschule Rosenheim}, year = {2008}, abstract = {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.}, language = {en} } @inproceedings{SchmidtWongYeap2007, author = {Schmidt, Jochen and Wong, C.K. and Yeap, W.K.}, title = {Spatial Information Extraction for Cognitive Mapping with a Mobile Robot.}, series = {Conference on Spatial Information Theory: COSIT'07, Melbourne, Australia. Volume 4736 of Lecture Notes in Computer Science}, booktitle = {Conference on Spatial Information Theory: COSIT'07, Melbourne, Australia. Volume 4736 of Lecture Notes in Computer Science}, year = {2007}, abstract = {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.}, language = {en} } @article{SchmidtWongYeap2007, author = {Schmidt, Jochen and Wong, C.K. and Yeap, W.K.}, title = {Localisation and Mapping with a Mobile Robot Using Sparse Range Data}, series = {Autonomous Robots and Agents, Studies in Computational Intelligence (SCI),}, journal = {Autonomous Robots and Agents, Studies in Computational Intelligence (SCI),}, publisher = {Springer}, year = {2007}, abstract = {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.}, language = {de} } @inproceedings{WongYeapSchmidt2007, author = {Wong, C.K. and Yeap, W.K. and Schmidt, Jochen}, title = {Using a Mobile Robot for Cognitive Mapping}, series = {International Joint Conference on Artificial Intelligence (IJCAI), pages 2243-2248, Hyderabad, India, 2007}, booktitle = {International Joint Conference on Artificial Intelligence (IJCAI), pages 2243-2248, Hyderabad, India, 2007}, year = {2007}, abstract = {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.}, language = {en} } @book{Schmidt2006, author = {Schmidt, Jochen}, title = {3-D Reconstruction and Stereo Self-Calibration for Augmented Reality}, publisher = {Logos}, address = {Berlin}, publisher = {Technische Hochschule Rosenheim}, year = {2006}, abstract = {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.}, language = {en} } @inproceedings{ZinsserSchmidtNiemann2003, author = {Zinßer, T. and Schmidt, Jochen and Niemann, H.}, title = {Performance Analysis of Nearest Neighbor Algorithms for ICP Registration of 3-D Point Sets}, series = {Vision, Modeling, and Visualization 2003}, booktitle = {Vision, Modeling, and Visualization 2003}, year = {2003}, abstract = {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.}, language = {en} } @article{ZobelDenzlerHeigletal.2003, author = {Zobel, M. and Denzler, J. and Heigl, B. and N{\"o}th, E. and Paulus, D. and Schmidt, Jochen and Stemmer, G.}, title = {MOBSY: Integration of vision and dialogue in service robots}, series = {Machine Vision and Applications}, journal = {Machine Vision and Applications}, year = {2003}, abstract = {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.}, language = {en} }