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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Noah Wach, Manuel Rudolph, Fred Jendrzejewski, Sebastian Schmitt,
"Data Re-Uploading on with a single qudit",
Quantum Machine Intelligence, 2023.
Abstract
Quantum two-level systems, i.e. qubits, form the basis for most quantum machine learning approaches that have been proposed throughout the years. However, in some cases, higher dimensional quantum systems may prove to be advantageous. Here, we explore the capabilities of multi-level quantum systems, so-called qudits, for their use in a quantum machine learning context.
We formulate classification and regression problems with the data re-uploadi...
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Christiane Wiebel and Martina Hasenjäger,
"Exploring the Relationship Between Gaze and Movement Transitions During Natural Human Walking on Different Terrains",
44th European Conference on Visual Perception, 2023.
Abstract
Understanding and predicting human walk behavior is an important prerequisite for a proper design of physical assist robot control. One challenge for such systems is the accurate and timely prediction of walk transitions. To improve models based on gait behavior only, prior work has investigated the effect of exploiting visual sensor data. Only few works have included human visual behavior, even though gaze plays a significant role for successful...
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Thomas Weisswange, Joel Schwartz von Sproutel, Aaron Horowitz, Jens Schmüdderich,
"Telepresence Lantern - Designing an Immersive Video-Mediated Communication Device for Older Adults",
ArXiv.org, 2023.
Abstract
We present the “Telepresence Lantern” concept, developed to provide opportunities for older adults to stay in contact with remote
family and friends. It provides a new approach to video-mediated communication, designed to facilitate natural and ambient
interactions with simplified call setup. Video communication is an established way to enhance social connectedness, but
traditional approaches create a high friction ...
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Nikolas Hohmann, Sebastian Brulin, Jürgen Adamy, Markus Olhofer,
"Three-Dimensional Urban Path Planning for Aerial Vehicles Regarding Many Objectives",
IEEE Open Journal on Intelligent Transportation Systems, vol. 4, pp. 639-352, 2023.
Abstract
Planning flight paths for unmanned aerial vehicles in urban areas requires consideration of safety, legal, and economic aspects as well as attention to social factors for gaining public acceptance. To solve this many-objective path planning problem in the three-dimensional space, we propose a hybrid framework combining an exact Dijkstra search and a metaheuristic evolutionary optimization. Given a start and an endpoint, we optimize a path regardi...
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