Tobias Rodemann, Hiroaki Kataoka , Thomas Jatschka, Guenther Raidl, Steffen Limmer, Hiromu Meguro,
"Optimizing the positions of battery swapping stations - Pilot studies and layout optimization algorithm ",
International Electric Vehicle Technology Conference (EVTeC) 2023, 2023.
Abstract
For electric scooters, battery swapping is a promising alternative to battery charging due to the lower weight and volume of their batteries that allow a manual replacement at battery swapping stations. Mobile batteries are shared between all users and the target of the operator is therefore to maximize the customer satisfaction while minimizing system set-up and operation costs. Here we give an overview of Honda’s activities for a Battery as a...
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Anna Belardinelli,
"Action in the eye of the beholder: what the gaze reveals about intentions and how it can be used",
NA, 2023.
Abstract
This is an invited talk at the University Carlos III Madrid...
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Christian Internó,
"Robust Non-Intrusive Load Monitoring for Industrial settings with high fidelity Simulations and Deep Learning ",
Universita degli Studi di Milano-Bicocca , 2023.
Abstract
Nowadays, we are observing the fourth industrial revolution 4.0, which integrates new production technologies to increase productivity and production quality. As a result, new Smart Companies are emerging, with data monitoring systems that are increasingly advanced and interconnected. Therefore, there is a growing need to develop advanced energy monitoring techniques to identify machinery behaviors by observing time series of generated data. Mode...
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Christopher Mower, Theodoros Stouraitis, Joao Moura, Christian Rauch, Lei Yan, Nazanin Behabadi, Michael Gienger, Tom Vercauteren, Christos Bergeles, Sethu Vijayakumar,
"ROS-PyBullet Interface: A framework for reliable contact simulation and human-robot interaction",
Conference on Robot Learning, 2023.
Abstract
Reliable contact simulation plays a key role in the development of (semi-) autonomous robots, especially when dealing with contact-rich manipulation scenarios, an active robotics research topic. Besides simulation, components such as sensing, perception, data collection, robot hardware control, human interfaces, etc. are all key enablers towards applying machine learning algorithms or model-based approaches in real world systems. However, there i...
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Jonathan Jakob, André Artelt, Martina Hasenjäger, Barbara Hammer,
"Interpretable SAM-kNN Regressor for Incremental Learning on High-Dimensional Data Streams",
Applied Artificial Intelligence, vol. 37, no. 1, 2023.
Abstract
In many real world scenarios, data is provided as a potentially infinite stream of samples, that are subject to changes in the underlying data distribution, a phenomenon often referred to as concept drift. A specific facet of concept drift is feature drift, where the relevance of a feature to the problem at hand changes over time.
High-dimensionality of the data poses an additional challenge to learning algorithms operating in such environments....
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Steffen Limmer, Johannes Varga, Guenther Raidl,
"An Evolutionary Approach for Scheduling a Fleet of Shared Electric Vehicles",
Applications of Evolutionary Computation 2023, Springer Nature Switzerland, pp. 3-18, 2023.
Abstract
In the present paper, we investigate the management of a fleet of electric vehicles. We propose a hybrid evolutionary approach for solving the problem of simultaneously planning the charging of electric vehicles and the assignment of electric vehicles to a set of reservations. The reservation assignment is optimized with an evolutionary algorithm while linear programming is used to compute optimal charging schedules. The evolutionary algorithm us...
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Can Wang, Mitra Baratchi, Thomas Bäck, Holger Hoos, Steffen Limmer, Markus Olhofer,
"Towards time series feature engineering in automated machine learning for multi-step forecasting",
Proc. of International Conference on Time Series and Forecasting (ITISE2022), vol. 18, no. 1, 2022.
Abstract
Feature engineering is an essential step in the pipelines used for many machine learning tasks, including time-series forecasting. Although existing AutoML approaches partly automate feature engineering, they do not support specialised approaches for time-series data such as multi-step forecasting. Multi-step forecasting is the task of predicting a sequence of values in a time series. Two kinds of approaches are commonly used for multi-step forec...
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Nikolas Hohmann, Mariusz Bujny, Jürgen Adamy, Markus Olhofer,
"Multi-objective 3D Path Planning for UAVs in Large-Scale Urban Scenarios",
IEEE Congress on Evolutionary Computation, 2022.
Abstract
In the context of real-world path planning applications for Unmanned Aerial Vehicles (UAVs), aspects such as handling of multiple objectives (e.g., minimizing risk, path length, travel time, energy consumption, or noise pollution), generation of smooth trajectories in 3D space, and the ability to deal with urban environments have to be taken into account jointly by an optimization algorithm to provide practically feasible solutions. Since the cur...
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Rodrigo Canaan, Xianbo Gao, Julian Togelius, Andy Nealen, Stefan Menzel,
"Generating and Adapting to Diverse Ad-Hoc Partners in Hanabi",
IEEE Transactions on Games, 2022.
Abstract
Hanabi is a cooperative game that brings the problem of modeling other players to the forefront. In this game, coordinated groups of players can leverage pre-established conventions to great effect. In this paper, we focus on ad-hoc settings with no previous coordination between partners. We introduce a “Bayesian Meta-Agent” that maintains a belief distribution over hypotheses of partner policies. The policies that serve as initial hypotheses...
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Thomas Schmitt, Matthias Hoffmann, Tobias Rodemann, Jürgen Adamy,
"Incorporating Human Preferences in Decision Making for Dynamic Multi-Objective Optimization in Model Predictive Control",
Inventions 2022, vol. 7, no. 3, 2022.
Abstract
We present a new two-step approach for automatized a posteriori decision making in multi-objective
optimization problems. In the first step, a knee region is determined based on the normalized Euclidean
distance from a hyperplane defined by the furthest Pareto solution and the negative unit vector. The size of
the knee region depends on the Pareto front’s shape and a design parameter. In the second step, preferences
for all objectives formu...
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