Search our Publications
Latest Publications
Kaosisochukwu Egbuonu , "Bayesian Network-based Intention Estimation of Traffic Participants ", Technical University of Darmstadt, 2024.
AbstractAutonomous vehicles are seen as a great source of hope when it comes to improving general road traffic safety. In order to achieve this and prevent potential accidents, they are required to predict the motion of surrounding traffic participants. Generally speaking, the movement of traffic participants is driven by hidden intentions such as taking a left turn or going straight at an intersection. Therefore, this work aims to develop an approach to...
Download Bibtex file Per Mail Request
Ahmed Sadik, Sebastian Brulin, Markus Olhofer, Antonello Ceravola, Frank Joublin , "LLM as a code generator in Agile Model Driven Development", Springer , 2024.
AbstractLeveraging Large Language Models (LLM) like GPT-4 in the auto-generation of code represents a signifi cant advancement, yet it is not without its challenges. The ambiguity inherent in natural language descriptions of software poses substantial obstacles to generating deployable, structured artifacts. This research champions Model-Driven Development (MDD) as a viable strategy to overcome these challenges, proposing an Agile Model-Driven Developmen...
Download Bibtex file Per Mail Request
Frank Joublin, Antonello Ceravola, Pavel Smirnov, Felix Ocker, Jörg Deigmöller, Anna Belardinelli, Chao Wang, Daniel Tanneberg, Stephan Hasler, Michael Gienger , "CoPAL: Corrective Planning of Robot Actions with Large Language Models", International Conference on Robotics and Automation (ICRA), 2024.
AbstractRecent advances in the field of pretrained Large Language Models (LLM) made commonsense knowledge available "out of the box" for a vast range of scenarios including content generation, customer service, and voice assistants. The release of GPT-3.5 (known as ChatGPT) opened prospectives for building highly contextualizable conversational agents, capable to hold a dialog and reflect about various situations as well as on behalf of different ...
Download Bibtex file Download PDF
Sebastian Schmitt , "Quantum multi-objective optimization ", QC Workshop 2024: GI Quantum Computing Workshop 2024, 2024.
AbstractSolving combinatorial optimization problems using variational quantum algorithms to be executed on near-term quantum devices has gained a lot of attraction in recent years. Currently, most works have focused on single-objective problems. In contrast, many real-world problems need to consider multiple conflicting objectives simultaneously, which is not well studied using variation quantum algorithms. In multi-objective optimization, one seeks the ...
Download Bibtex file Per Mail Request
Nikolas Hohmann, Sebastian Brulin, Jürgen Adamy, Markus Olhofer , "Multi-objective Optimization of Urban Air Transportation Networks under Social Considerations", IEEE Open Journal of Intelligent Transportation Systems, vol. 5, pp. 589 - 602, 2024.
AbstractThe growing urbanization and traffic density in cities call for efficient transportation solutions. One potential solution extends urban traffic into the airspace, requiring some kind of aerial infrastructure. This work addresses the problem of optimizing an aerial traffic network regarding multiple objectives. Given logistic hub positions and a set of optimized paths between them, we aim for a Pareto-optimal air corridor network structure. Th...
Download Bibtex file Download PDF
Tobias Rodemann and Christiane Attig , "How can digital twins help to accelerate the transition to a carbon-neutral energy system", EuroCAST (Computer Aided System Theory), 2024.
AbstractGood investment decisions into green energy systems are hard due to high budget requests, complex systems and multiple objectives to consider. Simulation models of current and potential future energy systems (so called digital twins) can help to generate a deeper understanding, better recommendations, and more reliable forecasts of costs and savings. We developed detailed simulation models for our R&D facility (see Fig. 1) using a simulation appr...
Download Bibtex file Per Mail Request
Anna Belardinelli, Chao Wang, Daniel Tanneberg, Stephan Hasler, Michael Gienger , "Train your robot in AR: investigating user experience with a continuously learning robot", Lifelong Learning and Personalization in Long-Term Human-Robot Interaction (LEAP-HRI), 2024.
AbstractAssistive robots that can be deployed in our homes will need to be understandable, operable, and teachable by non-expert users. This calls for an intuitive Human-Robot Interaction approach that is also safe and sustainable in the long term. Still, few studies have looked at repeated, unscripted interactions in a loosely supervised setting with a robot incrementally learning from the user and con- sequentially expanding its knowledge and abi...
Download Bibtex file Download PDF
Christiane Wiebel, Petros Georgiadis, Martina Hasenjäger , "On the role of eye and head movements for walk transitions in real world urban scenes ", 46th European Conference on Visual Perception (ECVP), 2024.
AbstractHuman gaze behavior plays a significant role for successful goal-directed locomotion. Yet, it has been rarely employed in multimodal models for predicting real-world human walk behavior. In this study, we set out to investigate its potential for improving the prediction of upcoming walk mode transitions in real-world urban scenes. We use a publicly available data set including IMU motion data and gaze data from the Pupil Labs Invisible eye tracke...
Download Bibtex file Per Mail Request
Fan Zhang and Michael Gienger , "Affordance-based Robot Manipulation with Flow Matching", Arxiv, 2024.
AbstractWe present a framework for assistive robot manipulation, which focuses on two fundamental challenges: first, effi- ciently adapting large-scale vision-language models to down- stream scene affordance understanding tasks, especially in daily living scenarios where gather multi-task data involving human requires strenuous effort; second, effectively learning robot trajectories by grounding the visual affordance model. We tackle the first cha...
Download Bibtex file Per Mail Request
Michael Gienger , "Robot Assistance with Large Language Models", Workshop "Learning for Assistive Robots" of the 2024 Robotics Science and Systems Conference, 2024.
AbstractSummary talk about 2 papers with respect to robot assistance: CoPAL: Corrective Planning of Robot Actions with Large Language Models and To Help or Not to Help: LLM-based Attentive Support for Human-Robot Group Interactions. ...
Download Bibtex file Per Mail Request
1 ... 5 6 7 8 9 10 ... 170
Follow us
