Search our Publications
Latest Publications
Jennifer Kreger, Stephan Hasler, Ute Bauer-Wersing , "Simultaneous Interactive Learning of Identities and Attributes of Objects in an Autonomous Mobile Robot's Environment", Fourth International Workshop on Intrinsically-Motivated Open-ended Development (IMOL2019), 2019.
AbstractIn the extended abstract we describe our system of autonomous robots cooperating with humans. The robots provide tasks concerning different objects in the environment (e.g. bringing them somewhere), thus they must be able to communicate with the user about them. Hence, the robots have to recognize identities of objects, but also handle unknown objects by describing them with their attributes or understanding attribute-based descriptions of these ...
Download Bibtex file Per Mail Request
Andrea Castellani , "Real-world Anomaly Detection by using Digital Twin systems and Deep Learning algorithms", Univ. delle Marche, Ancona, 2019.
AbstractNowdays, with the continuously growing of monitored data present in Smart Company environment, the need of some anomaly detection technique is became more relevant, in order identify some anomalous behavior from time series data generated by sensors. With a Digital Twin, a detailed simulation of a complex physical object or system, is possible to provide more data to feed in a machine learning algorithm and thus help in the anomaly detection ...
Download Bibtex file Per Mail Request
Duc Nguyen, Steffen Limmer, Kaifeng Yang, Markus Olhofer, Thomas Bäck , "Modelling and Prediction of Remaining Useful Lifetime for Maintenance Scheduling Optimization of a Car Fleet", International Journal of Performability Engineering, vol. 15, no. 9, 2019.
AbstractThe remaining useful lifetime (RUL) is the time remaining until an asset no longer meets operational requirements. An accurate estimation of the RUL is central to prognostics and health management systems. However, the RUL of an asset is usually very difficult to estimate and to achieve in any industry. This is because the RUL strongly depends on manufacturing, the operating environment, and the observed condition monitoring. Here, we use physics...
Download Bibtex file
Guo Yu, Yaochu Jin, Markus Olhofer , "An a priori Knee Identification Multi-objective Evolutionary Algorithm Based on α-Dominance", Proceedings of the Genetic and Evolutionary Computation Conference Companion, {GECCO} 2019, pp. 241-242, 2019.
AbstractIn the preference-based multi-objective optimisation, the lack of priori-knowledge makes it difficult for the decision maker to specify an informed preference. Thus, the knees are regarded as the naturally preferred solutions on the Pareto optimal front where a small improvement in some objectives will seriously deteriorate other objectives. However, most research is based on a given large number of solutions and a posteriori identifies the knee ...
Download Bibtex file
Matti Krüger , "Invited talk at Bielefeld University - Seminar "Autonomous Driving"", Seminar: Autonomous Driving, 2019.
AbstractThe seminar "Autonomous Driving" deals with the following topics: 1. Pipeline, sensor setup, benchmarks, sensor fusion 2. Object recognition and tracking, driver behavior analysis 3. Localization, mapping, planning 4. Car-to-X communication, validation, end-to-end AD, ethics and social acceptance . In the talk I am going to introduce exemplary projects from HRI which suit many of the topics listed above (HARP, iACC, iTFP+fairness, risk map...
Download Bibtex file Per Mail Request
Pouya Aghaei-Pour, Tobias Rodemann, Markus Olhofer, Jussi Hakanen, Kaisa Miettinen , "Surrogate Assisted Interactive Multiobjective Optimization in Building Energy System Design", 25th International Conference on Multiple Criteria Decision Making , 2019.
AbstractManagers of larger buildings are confronted with complex investment decisions concerning possible extensions of the energy system, like photo voltaics(PV), stationary batteries or heat storage. They have to consider a multitude of objectives, for example, investment and annual operation costs, CO2 emissions and module lifetime. A computer-assisted optimization and decision making process promises substantial benefits in this complex problem. In t...
Download Bibtex file Per Mail Request
Sina Däubener, Sebastian Schmitt, Hao Wang, Thomas Bäck, peter krause , "Large Anomaly Detection in Univariate Time Series: An Empirical Comparison of Machine Learning Algorithms", 19th Industrial Conference on Data Mining ICDM 2019, 2019.
AbstractThis paper presents an empirical comparison of state-of-the-art machine learning and statistical methods for anomaly detection in univariate time series. In particular, we compare random forests, support vector machines, $k$-nearest neighbour regression, artificial neural networks, long short-term memory networks, Twitter's anomaly detection method AdVec and an ARIMA model on publicly available data sets with labeled anomalies. Since the anoma...
Download Bibtex file
Michael J. Mathew, Saif Sidhik, Mohan Sridharan, Morteza Azad, Akinobu Hayashi, Jeremy Wyatt , "Online Learning of Feed-Forward Models for Variable Impedance Control in Manipulation Tasks", Robotic Science and System: Workshop on Task-Informed Grasping, 2019.
AbstractWhile performing a new manipulation task, humans tend to be stiffer in the initial trials to improve task accuracy and to counter any disturbances that may affect task performance. After a sufficient number of repetitions, humans are able to perform the task with lower stiffness without causing any significant reduction in task performance. Existing literature in human and animal motor control indicates that learned internal models of the manipul...
Download Bibtex file
Martin Ernst Heckmann, Heiko Wersing, Dennis Orth, Dorothea Kolossa, Nadja Schömig, Mark Dunn , "DEVELOPMENT OF A COOPERATIVE ON-DEMAND INTERSECTION ASSISTANT-CONCEPT EVALUATION, PERSONALIZATION AND PROTOTYPE IMPLEMENTATION- ", International Journal of Automotive Engineering, vol. 10, no. 2, pp. 175-183, 2019.
AbstractIn this paper we present our recently introduced “assistance on demand (AOD)” concept, which allows the driver to request assistance via speech whenever he or she deems it appropriate. The target scenario we currently investigate is turning left from a subordinate road in dense urban traffic. We first compare our system in a driving simulator study to driving without assistance or with visual assistance. The results show that drivers clearly pref...
Download Bibtex file
Julian Eggert, Jörg Deigmöller, Lydia Fischer, Andreas Richter , "Memory Nets: Knowledge Representation for Intelligent Agent Operations in Real World", International Conference on Knowledge Engineering and Ontology Development, 2019.
AbstractIn this paper, we introduce Memory Nets, a knowledge representation targeted at Autonomous Intelligent Agents (IAs) operating in real world. The main focus is on a knowledge base (KB) that on the one hand is able to leverage the large body of openly available semantic information, and on the other hand allows to incrementally accumulate additional knowledge from situated interaction. Such a KB can only rely on operable semantics fully contained ...
Download Bibtex file
1 ... 80 81 82 83 84 85 ... 183
Follow us
