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Simon Manschitz, Michael Gienger, Jens Kober, Jan Peters , "Probabilistic Decomposition of Sequential Force Interaction Tasks into Movement Primitives", IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016.
AbstractLearning sequential force interaction tasks from kinesthetic demonstrations is a promising approach to transfer human manipulation abilities to a robot. In this paper we propose a novel concept to decompose such demonstrations into a set of Movement Primitives (MPs). The decomposition is based on a probability distribution we call Directional Normal Distribution (DND). To capture the sequential properties of the manipulation task, we model the de...
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Andrea Schnall and Martin Ernst Heckmann , "Balancing Gaussianity and sparseness in feature-space speaker adaptation for word prominence detection", 12. ITG Fachtagung Sprachkommunikation, 2016.
AbstractProsodic cues are an important tool of human communication. One of this cues is the word prominence, which we are using to express e.g. important information. Nevertheless in human-machine communication such cues are rarely used. One problem for usage in speech processing is the large difference between different speakers. To overcome this problem, a common method is an adaptation of the new data to the trained model. Since for problem cas...
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Nils Magiera, Herbert Janßen, Hermann Winner , "An Approach for Automatic Riding Skill Identification - Methodology and first Results", Ifz Konferenz 2016, 2016.
AbstractDue to the static and dynamic instabilities of a motorcycle the rider performs a highly demanding control task during e.g. cornering, braking or a combination of both. Thus safety and comfort of the ride strongly depend on the personal abilities and skills of the rider. As a result existing Advanced-Rider-Assistance-Systems for powered two-wheelers try to improve both safety and comfort by taking rider characteristics into account and warn or int...
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Nils Magiera, Herbert Janßen, Martin Ernst Heckmann, Hermann Winner , "Rider Skill Identification by Probabilistic Segmentation into Motorcycle Maneuver Primitives", 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC 2016), 2016.
AbstractAs a result of the static and dynamic instabilities of a Powered-Two-Wheeler the rider performs a highly demanding control task. Rider safety strongly depends on individual abilities and skills of the rider. To improve the riders’ skill level and reduce riding errors, safety trainings are well established. Additionally safety systems and recently also advanced rider assistance systems help to avoid or m...
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Jennifer Kreger, Lydia Fischer, Stephan Hasler, Ute Bauer-Wersing, Thomas H Weisswange , "Quality Prediction for a Road Detection System", New Challenges in Neural Computation (NC2), 2016.
AbstractMachine learning algorithms are used for autonomous driving systems, but they cannot always offer reliable results. We propose an approach to predict the credibility of such a system without knowing the system itself in detail. Based on the prediction, poor results can be rejected to raise the overall quality of the system. We show that our approach excels a traditional rejection strategy for road detection. ...
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Edoardo Casapietra, Thomas H Weisswange, Christian Goerick, Franz Kummert , "Enriching a Spatial Road Representation with Lanes and Driving Directions", IEEE 19th Intelligent Transportation Systems Conference (ITSC 2016), 2016.
AbstractThe detection of lane layout in the surroundings of the ego-vehicle is a key issue for modern ADAS and autonomous driving. Most modern systems rely on annotated spatial maps to provide lane information. However, these maps are not available everywhere, and thus have to be often supported by direct detection systems (e.g. cameras, lasers). Such systems detect lane boundaries by directly observing lane markings or sensing curbstones and pavements. ...
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Tobias Rodemann, Lars Gräning, Ken Nishikawa , "Automatic Energy Management Controller Design for Hybrid Electric Vehicles", Computational Intelligence (SSCI), 2016 IEEE Symposium Series on, pp. 1-8, 2016.
AbstractDue to strict CO2 emission limits, the optimal design of controllers for hybrid cars is an increasingly important topic. Most current approaches use engineers' knowledge to develop controllers. In this work we evaluate how simple control rules can automatically be extracted from optimal controls computed by Dynamic Programming (DP). We compare artificial neural networks and decision trees in terms of performance (fuel consumption), stability, ro...
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Lea Schönherr, Dennis Orth, Martin Ernst Heckmann, Dorothea Kolossa , "Environmentally Robust Audio-Visual Speaker Identification", IEEE Workshop on Spoken Language Technology, 2016.
AbstractTo improve the accuracy of audio-visual speaker identification, we propose a new approach, which achieves an optimal combination of the different modalities on the score level. We use the i-vector method for the acoustics and the local binary pattern (LBP) for the visual speaker recognition. Regarding the input data of both modalities, multiple confidence measures are utilized to calculate an optimal weight for the fusion. Thus, oracle weights ar...
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Viktor Losing, Barbara Hammer, Heiko Wersing , "KNN classifier with self adjusting memory for heterogenous concept drift", IEEE International Conference on Data Mining, 2016.
AbstractLearning from non-stationary data streams is gaining more attention recently, especially in the context of Internet of Things and Big Data. It is a highly challenging task, since the fundamentally different types of possibly occurring drift undermine classical assumptions such as i.i.d data. Incremental drift characterizes a continuous change in the distribution such as the signals of a slowly degrading sensor. A suddenly malfunctioning sen...
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Timo Friedrich, Martin Heiderich, Minh-Tri Nguyen , "New approach for improvement of vehicle performance by using a simulation-based optimization and evaluation method ", 7th International Munich Chassis Symposium 2016: chassis.tech plus (Proceedings), 2016.
AbstractDue to increasing vehicle complexity and growing customer requirements, the early consideration and subjective evaluation of the overall vehicle performance is very important to identify weak points and keep the predefined development time. Complex problems can be investigated and optimized in the early development process using simulation-based working environments. Additionally first subjective evaluations without a real vehicle are possible ut...
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