Steffen Limmer,
"Bilevel Large Neighborhood Search for the Electric Autonomous Dial-a-Ride Problem",
Transportation Research Interdisciplinary Perspectives, vol. 21, 2023.
Abstract
The electric autonomous dial-a-ride problem (E-ADARP) represents a challenging and practically relevant extension of the dial-a-ride problem, which takes electric vehicle charging into account. It introduces battery constraints and the option to recharge vehicles at different charging stations. The present paper proposes a bilevel large neighborhood search approach (BI-LNS) for the E-ADARP. In the outer level of the proposed approach, charging se...
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Daniel Tanneberg and Michael Gienger,
"Learning Type-Generalized Actions for Symbolic Planning",
IEEE/RSJ International Conference on Intelligent Robots and Systems, 2023.
Abstract
Symbolic planning is a powerful technique to solve complex tasks that require long sequences of actions and can equip an intelligent agent with complex behavior.
The downside of this approach is the necessity for suitable symbolic representations describing the state of the environment as well as the actions that can change it.
Traditionally such representations are carefully hand-designed by experts for distinct problem domains, which limits t...
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Claudio Maffi and Jens Engel,
"Evaluation and comparison of PV prediction quality of a sky imager",
HRI-EU, 2023.
Abstract
On the premises of Honda R&D Germany in Offenbach, Main, a large photovoltaic (PV) system with a
peak power of 750kW is installed. The PV system is connected to an energy management system (EMS),
which manages how electric energy is distributed and stored in the building. In order to use efficiently
the green energy provided by the PV system into the EMS, accurate predictions about the accessibile PV
power are requested. Currently a meteorolo...
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Chao Wang and Derck Chu,
"Visualizing risk areas using augmented reality glasses as advanced driver-assistance system",
AUTO UI 23, 2023.
Abstract
In complex driving scenarios, drivers often face the challenge of making quick decisions regarding the safety of crossing intersections or entering roundabouts. These decisions, prone to human error, can compromise road safety and driving efficiency. The recent advancements in augmented reality (AR) glasses hold significant potential for assisting drivers in avoiding such dangers. Unlike traditional AR heads-up displays (HUDs), AR glasses provide...
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Muhammad Haris,
"Visual Localization and Mapping in Seasonally Changing Outdoor Environments",
UAS Frankfurt, 2023.
Abstract
Visual localization and mapping refer to locating an agent in a scene and creating a
representation of its surroundings using a camera as the primary source of perception.
Localization and mapping are the fundamental prerequisites for autonomous robots,
self-driving cars, and augmented reality applications. Despite decades of research
and development in this domain, even state-of-the-art vision-based approaches strug-
gle to perform in chall...
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Qiqi Liu, Felix Lanfermann, Tobias Rodemann, Markus Olhofer, Yaochu Jin,
"Surrogate-Assisted Many-objective Optimization of Building Energy Management",
IEEE Computational Intelligence Magazine, vol. 18, no. 4, pp. 14-28, 2023.
Abstract
Building energy management usually involves a number of objectives such as investment costs, thermal comfort, system resilience, battery life, and many others. However, most existing studies merely consider optimizing less than three objectives since it becomes increasingly difficult as the number of objective increases. In addition, the optimization of building energy management heavily relies on time-consuming energy simulators, posing great ch...
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Guo Yu, Yaochu Jin, Markus Olhofer, Qiqi Liu, Wenli Du,
"Solution Set Augmentation for Knee Identification in Multiobjective Decision Analysis",
IEEE Transactions on Cybernetics, vol. 53, no. 4, pp. 2480-2493, 2023.
Abstract
In multiobjective decision making, most knee identification algorithms implicitly assume that the given solutions are well distributed and can provide sufficient information for identifying knee solutions. However, this assumption may fail to hold when the number of objectives is large or when the shape of the Pareto front is complex. To address the above issues, we propose a knee-oriented solution augmentation (KSA) framework that converts the P...
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David Rother, Jan Peters, Thomas Weisswange,
"Disentangling Interaction using Maximum Entropy Reinforcement Learning in Multi-Agent Systems",
26th European Conference on Artificial Intelligence (ECAI 2023), pp. 1994-2001, 2023.
Abstract
Research on multi-agent interaction involving multiple humans is still in its infancy. Most recent approaches have focused on environments with collaboration-focused human behavior, or providing only a small, defined set of situations.
When deploying robots in general human-inhabited environments in the future it will be unlikely that all intentions can be guaranteed to fit a pre-defined model of collaboration while one might still expect a rob...
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Hesham Elsayed,
"Computer-Supported Posture and Movement Guidance - Investigating visual/visuotactile guidance and informing the
design of vibrotactile body-worn interfaces",
Technical University of Darmstadt, Technical University of Darmstadt, pp. 247, 2023.
Abstract
This dissertation explores the use of interactive systems to support
movement guidance, with applications in various fields such as sports,
dance, physiotherapy, and immersive sketching. The research focuses
on visual, haptic, and visuohaptic approaches and aims to overcome
the limitations of traditional guidance methods, such as dependence
on an expert and high costs for the novice. The main contributions of
the thesis are (1) an evaluatio...
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Tim Puphal,
"Risk Models for Driver Support and Autonomous Driving",
IEEE Intelligent Vehicle Symposium, IEEE Intelligent Vehicle Symposium, 2023.
Abstract
Journal talk about risk models for driver support and autonomous driving vehicles in the IEEE Intelligent Vehicles Symposium (IV 2023).
Recent works about risk models and different applications, such as driver support with Risk Maps, human models with Risk Maps and scalable autonomous driving with Risk Maps was presented.
This talk is an overview talk of the research from the last years about risk models....
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