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Thomas Schnürer, Stefan Fuchs, Horst-Michael Groß, "Real-Time 3D Pose Estimation from Single Depth Images ", 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 2019.

Abstract

To allow for safe Human-Robot-Interaction in industrial scenarios like construction plants, it is essential to always be aware of the location and pose of humans in the shared workspace. We introduce a real-time 3D pose estimation system using single depth images that is aimed to run on limited hardware, like, e.g. , a mobile robot. For this, we optimize a CNN-based 2D pose estimation architecture to achieve high frame rates while simultaneou...



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Tobias Rodemann and Kai Kitamura, "Simulation-based Design and Evaluation of a Smart Energy Manager", EuroCAST, 2019.

Abstract

Decreasing prices for Photo Voltaic (PV) systems promise an affordable solution for a low emission lifestyle. With the rise of electric mobility a sufficiently large PV system could even be used to power both private homes and Battery Electric Vehicles (BEVs). In practice, the fluctuating nature of PV systems requires a storage element to balance energy flows through periods of over-production (more power is produced than required) and no product...



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Thomas Jatschka, Tobias Rodemann, Guenther Raidl, "Comparing Machine Learning Models in a Cooperative Optimization Approach for Distributing Service Points", EuroCAST, 2019.

Abstract

We consider a variant of the facility location problem [2]. The task is to find an optimal subset of locations within a certain geographical area for erecting service points in order to satisfy customer demands as best as possible. This general scenario has a wide range of real-world applications. More specifically, we have the setup of stations for mobility purposes in mind, such as erecting bike sharing stations for a public bike sharing system...



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Tobias Rodemann, "A Comparison of Different Many-Objective Optimization Algorithms for Energy System Optimization", Applications of Evolutionary Computation, pp. 1-16, 2019.

Abstract

The usage of renewable energy sources, storage devices, and flexible loads has the potential to greatly improve the overall efficiency of a building complex or factory. However, one needs to consider a multitude of upgrade options and several performance criteria. We therefore formulated this task as a many-objective optimization problem with 10 design parameters and 5 objectives (investment cost, yearly energy costs, \CO emissions, system resil...



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Guo Yu, Yaochu Jin, Markus Olhofer, "Benchmark Problems and Performance Indicators for Search of Knee Points in Multi-objective Optimization", IEEE Transactions on Cybernetics, 2019.

Abstract

During the preference-based optimization, the decision makers (DMs) are hard to understand the problem without priori knowledge and give their preference information. Also, solutions have many features, and the searching space is very large and usually not homogenious. Depending on the features, the solutions are more less important, while important might be problem dependent. This can be eg. knee points, robust areas, etc. Therefore, the prefere...



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Elena Raponi, Mariusz Bujny, Markus Olhofer, Nikola Aulig, Simonetta Boria, Fabian Duddeck, "Kriging-Assisted Topology Optimization of Crash Structures", Computer Methods in Applied Mechanics and Engineering, 2019.

Abstract

Over the recent decades, Topology Optimization (TO) has become an important tool in the design and analysis of mechanical structures. Although structural TO is already used in many industrial applications, it needs much more investigation in the context of vehicle crashworthiness. Indeed, crashworthiness optimization problems present strong nonlinearities and discontinuities, and gradient-based methods cannot be applied. The aim of this work is t...



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Thomas Jatschka, Tobias Rodemann, Guenther Raidl, "A Cooperative Optimization Approach for Distributing Service Points in Mobility Applications", EvoCOP, pp. 1-16, 2019.

Abstract

We investigate a variant of the facility location problem concerning the optimal distribution of service points with incomplete information within a certain geographical area. The application scenario is generic in principle, but we have the setup of charging stations for electric vehicles or rental stations for bicycles or cars in mind. When planning such systems, estimating under which conditions which customer demand can be fulfilled is fundam...



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Akinobu Hayashi, Dirk Ruiken, Christian Goerick, Tadaaki Hasegawa, "Online adaptation of uncertain models using neural network priors and partially observable planning", International Conference on Robotics and Automation (ICRA) 2019, 2019.

Abstract

One of the key challenges in realizing a robot that is capable of completing a variety of manipulation tasks in the real world is the need to utilize sufficiently compact and rich world models. If the assumed prediction model does not match real observations, planning systems are unable to perform properly. We propose a system that corrects the models based on information collected from the robot's sensors. We encode prior experiences in a neural...



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Viktor Losing, Martina Hasenjäger, Heiko Wersing, Barbara Hammer, "Personalized Online Learning of Whole-Body Motion Classes Using Multiple Inertial Measurement Units", International Conference on Robotics and Automation (ICRA), 2019.

Abstract

Online action classification is an important field of research, enabling the particularly interesting application scenario of controlling wearable devices which actively support the user's motions. The majority of machine learning applications of real-world systems are based on pre-trained average-user models without any personalization. Our long-term goal is to provide a system that adapts to its user's personal behavior patterns on the fly and ...



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Guo Yu, Yaochu Jin, Markus Olhofer, "References or Preferences – Rethinking Many-objective Evolutionary Optimization", CEC 2019, 2019.

Abstract

Past decades have witnessed a rapid development in multi- and many-objective evolutionary optimization. The references-assisted and preference-driven strategies are both widely used in dealing with the multi- and many-objective optimization problems. However, few research analyzes the difference between these two strategies. Thus, this paper analyzes and compares both strategies from background, constructions, similarities, differences, to concer...



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