Sebastian Brulin, Mariusz Bujny, Tim Puphal, Stefan Menzel,
"Evolutionary Algorithms for eVTOL Design Optimization based on Multi-agent Simulations",
MATSim User Meeting 2022, 2022.
Abstract
In urban and regional air mobility, technological advances open up the utilization of new mobility concepts in the foreseeable future. The introduction of a new mobility system brings many challenges, from vehicle specifications to air traffic control architectures, from traffic safety to affordability and availability, and many more. This paper tackles the first problem by identifying an optimal electric vertical takeoff and landing (eVTOL) airc...
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Jens Engel, Thomas Schmitt, Tobias Rodemann, Jürgen Adamy,
"Hierarchical Economic Model Predictive Control Approach for a Building Energy Management System With Scenario-Driven EV Charging",
IEEE Transactions on Smart Grid, vol. 13, no. 4, pp. 3082 - 3093, 2022.
Abstract
To deal with the increasing number of EVs and their effect on the infrastructure, intelligent and coordinated charge management is necessary. In this paper, this problem is considered in the context of a commercial building energy management system (BEMS) with V2G-capable employee EV charging stations (EVCS). We propose a hierarchical economic model predictive control (EMPC) scheme for the operation of the BEMS and the integration of EV charge ma...
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Charlie Street, Bruno Lacerda, Manuel Mühlig, Nick Hawes,
"Proactive Multi-Robot Task Allocation Under Spatiotemporal Uncertainty",
Autonomous Robots and Multirobot Systems (ARMS) 2022, 2022.
Abstract
Multi-robot task allocation methods should be robust to task
announcements during execution, where task announcement times and
locations are uncertain. In this paper, we model task announcement us-
ing continuous-time Markov chains which can be learned from empirical
data. We then evaluate announcement time and location distributions
through model checking techniques. To service uncertain tasks efficiently,
allocation should occur proactive...
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Nils Einecke and Thomas Weisswange,
"Detecting Availability to Facilitate Social Communication",
ICRA Workshop: Exploring the Roles of Robots for Embodied Mediation, 2022.
Abstract
Modern communication has shifted strongly towards the digital domain. Technologies like chat applications and messengers provide means to connect with anyone at anytime. However, being always reachable can create stress and provides potential for social pressure due to expected timely responses. In contrast, the classical communication types via telephone is based on dedicated time slots for an ongoing communication, but suffers from the need to ...
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Moritz Bühler,
"Theory of mind and information relevance in human centric human robot cooperation",
Technical University Darmstadt, Technical University Darmstadt, 2022.
Abstract
In the interaction with others, besides consideration of environment and
task requirements, it is crucial to account for and develop an understand-
ing for the interaction partner and her state of mind. An understanding
of other’s state of knowledge and plans is important to support efficient
interaction activities including information sharing, or distribution of sub-
tasks.
A robot cooperating with and supporting a human partner might d...
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Qiqi Liu, Yaochu Jin, Martin Heiderich, Tobias Rodemann,
"Surrogate-Assisted Evolutionary Optimization of Expensive Many-objective Irregular Problems",
Knowledge-Based Systems, vol. 240, pp. 108197, 2022.
Abstract
Surrogate-assisted evolutionary algorithms are one effective approach to handling expensive problems and have attracted increasing attention over the past decades. However,
existing surrogate-assisted evolutionary algorithms pay little attention to expensive many-objective problems with irregular Pareto fronts, also called irregular problems. In this study, we
propose a surrogate-assisted evolutionary algorithm for dealing with expensive irregu...
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Simon Manschitz and Dirk Ruiken,
"Shared Autonomy for Intuitive Teleoperation",
ICRA Workshop: Shared Autonomy in Physical Human-Robot Interaction: Adaptability and Trust, 2022.
Abstract
Shared autonomy can be a means for combining the strengths and alleviating the weaknesses of two heterogeneous agents. In a teleoperation system with shared autonomy, a robotic system can take over the control from the human operator in certain situations, for instance when the operator has issues controlling the robot due to diminished depth perception. However, it is often difficult to decide when and how to take over control. In this paper, we...
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Steffen Limmer and Nils Einecke,
"An Efficient Approach for Peak-load-aware Scheduling of Energy-intensive Tasks in the Context of a Public IEEE Challenge",
Energies, vol. 15, no. 10, 2022.
Abstract
The shift towards renewable energy and decreasing battery prices have led to numerous installations of PV and battery systems in industrial and public buildings. Furthermore, the fluctuation of energy costs is increasing since energy sources based on solar and wind power depend on the weather situation. In order to reduce energy costs, it is necessary to plan energy-hungry activities while taking into account private PV production, battery capaci...
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Sneha Saha, Leandro Minku, Xin Yao, Bernhard Sendhoff, Stefan Menzel,
"Split-AE: An Autoencoder-based Disentanglement Framework for 3D Shape-to-shape Feature Transfer",
International Joint Conference on Neural Networks (IJCNN), 2022.
Abstract
Recent advancements in machine learning comprise generative models such as autoencoders (AE) for learning and compressing 3D data to generate low-dimensional latent representations of 3D shapes. Learning latent representations that disentangle the underlying factors of variations in 3D shapes is an intuitive way to achieve generalization in generative models. However, it remains an open problem to learn a generative model of 3D shapes such that t...
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Nivesh Dommaraju, Mariusz Bujny, Stefan Menzel, Markus Olhofer, Fabian Duddeck,
"Cooperative multi-objective topology optimization using clustering and metamodelling",
IEEE 2022 Congress on Evolutionary Computation, 2022.
Abstract
Topology optimization optimizes material layout in
a design space for a given objective, such as crash energy
absorption, and a set of boundary conditions. In industrial applications, multi-objective topology optimization requires expensive
simulations to evaluate the objectives and generate multiple
Pareto-optimal solutions. So, it is more economical to identify
preferred regions on the Pareto front and generate only the
desired solutions....
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