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Thomas Jatschka, Tobias Rodemann, Guenther Raidl , "Exploiting Similar Behavior of Users in a Cooperative Optimization Approach for Distributing Service Points in Mobility Applications", Machine Learning, Optimization, Data Science (LOD), no. 11943, pp. 738-750, 2020.
AbstractIn this contribution we address scaling issues of our previously proposed cooperative optimization approach (COA) for distributing service points for mobility applications in a geographical area. COA is an iterative algorithm that solves the problem by combining an optimization component with user interaction on a large scale and a machine learning component that provides the objective function for the optimization. In each iteration candidate so...
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Xilu Wang, Sebastian Schmitt, Markus Olhofer, Yaochu Jin , "Transfer Learning for Gaussian Process Assisted Evolutionary Bi-objective Optimization for Objectives with Different Evaluation Times", GECCO 2020, 2020.
AbstractDespite the success of evolutionary algorithms (EAs) for solving multi-objective problems, most of them are based on the assumption that all objectives can be evaluated within the same period of time. However, in many real-world ap- plications, such an assumption is unrealistic since diff erent objectives must be evaluated using diff erent computer simu- lations or physical experiments with various time complex- ity. To address this issue,...
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Linda Spaa, van der, Michael Gienger, Tamas Bates, Jens Kober , "Optimizing Ergonomics in Sequential Human-Robot Physical Cooperation Tasks ", ICRA 2020 / RA-L, 2020.
AbstractThis paper presents a method which incorporates human ergonomics in the optimization of sequential bi-manual physical human-robot interaction tasks. The physical interaction tasks comprise joint transport and rotation of objects too large to be handled in a comfortable or safe way by either robot or human alone. We predict the future ergonomic cost of the human partner in a task in which the robot has continuous physical interaction with this par...
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Sandra Ittner, Dominik Mühlbacher, Thomas H Weisswange , "The Discomfort of Riding Shotgun – Why Many People don't like to be Co-Driver", Frontiers in Psychology, vol. 11, no. 584309, 2020.
AbstractObjective: This work investigates which conditions lead to co-driver discomfort aside from classical motion sickness, what characterizes uncomfortable situations and why these conditions lead to discomfort. Background: The automobile is called a “passenger vehicle” as its main purpose is the transportation of people. However, passengers in the car are rarely considered in automotive research and especially in research about driving discomfort. T...
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Mariusz Bujny , "Research on Crashworthiness and Cooperative Topology Optimization at HRI-EU", Meeting at TU Delft (virtual), 2020.
AbstractDriven by rising competition on the market, strict emission regulations, and high customer expectations regarding vehicle safety, the complexity of the development process in automotive industry is constantly growing and leads to unintuitive design solutions accounting for a large number of load cases in multiple disciplines, different material types and manufacturing processes, and cost reduction by increasing commonality. In the conceptual desi...
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Skylar Sible, Rodrigo Iza-Teran, Jochen Garcke, Nikola Aulig, Patricia Wollstadt , "A compact spectral descriptor for shape deformations", 24th European Conference on Artificial Intelligence (ECAI 2020), vol. 325, pp. 1930 - 1937, 2020.
AbstractModern product development cycles are increasingly driven by the computational analysis of digital simulation models. Efficient simulation requires a suitable representation of the component or structure under development--typically a polygon surface mesh--, as well as an efficient representation of critical design criteria. In various application domains, one such criterion is the plastic deformation of a part under stress, which is commonly stu...
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Muhammad Haris, Mathias Franzius, Ute Bauer-Wersing, Karam Sai Krishna Kaushik , "Visual Localization and Mapping with Hybrid SFA", Conference on Robot Learning (CORL 2020), 2020.
AbstractVisual localization is a crucial requirement in mobile robotics, field and service robotics, and self-driving cars. Recently, unsupervised learning with Slow Feature Analysis (SFA) has shown to produce spatial representations that enable localization from holistic images. The approach is faster and much less complex than state-of-the-art monocular visual SLAM methods while achieving similar localization performance in small-scale environments. Ho...
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Jan Philip Goepfert, Barbara Hammer, Heiko Wersing , "Locally Adaptive Nearest Neighbours", European Symposium on Artificial Neural Networks ESANN, 2020.
AbstractWhen training automated systems, it has been shown to be beneficialto adapt the representation of data by learning a problem-specific metric.This metric is global. We extend this idea and, for the widely used familyof k nearest neighbors algorithms, develop a method that allows learninglocallyadaptive metrics. To demonstrate important aspects of how ourapproach works, we conduct a number of experiments on synthetic datasets, and we show its usefu...
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Moritz Bühler and Thomas H Weisswange , "Theory of Mind based Communication for Human Agent Cooperation ", IEEE International Conference on Human-Machine Systems, 2020.
AbstractFor human agent cooperation, reasoning about the partner is necessary to enable an efficient interaction. To provide helpful information, it is important not only to account for environmental uncertainties or dangers but also to maintain a sophisticated understanding of each other’s mental state, a theory of mind. Sharing every piece of information is not a good idea, as some may be irrelevant at time or already known, leading to distracti...
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Newton Masinde, Sebastian Bischoff, Kalman György Graffi , "Capacity Management Protocol for a Structured P2P-based Online Social Network", OSNT 2020: The 5th International Workshop on Online Social Networks Technologies, 2020.
AbstractPeer-to-peer (P2P) networks were first made popular by filesharing applications such as KaZaA, Napster, LimeWire and BitTorrent. These early applications on P2P networks relied exclusively on always connected users to ensure that the services were available by utilizing some form of centralized indexing services. With the rapid technological developments, the computing devices have become increasingly smaller and are connected via mobile networks...
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