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Felix Lanfermann , "Concept Identification for Complex Data Sets", Bielefeld University, 2023.
AbstractLarge and complex data sets play an essential role in many engineering and computer science applications. Revealing structures within data sets, such as groups of similar data samples or correlations between feature values, is often desirable. But generating such insights is far from trivial. The field of concept identification targets to automatically find groups of data samples in large and complex data sets which share common properties. Such ...
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Frank Joublin, Antonello Ceravola, Pavel Smirnov, Felix Ocker, Jörg Deigmöller, Anna Belardinelli, Chao Wang, Daniel Tanneberg, Stephan Hasler, Michael Gienger , "CoPal: Planning Robot Actions using Large Language Models", Arxiv, no. arXiv:2310.07263, 2023.
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 social ...
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Thiago de Jesus de Araujo Rios, Stefan Menzel, Bernhard Sendhoff , "Large Language and Text-to-3D Models for Engineering Design Optimization", IEEE Symposium Series on Computational Intelligence, 2023.
AbstractThe current advances in generative artificial intelligence for learning large neural network models with the capability to produce essays, images, music and even 3D assets from text prompts create opportunities for a manifold of disciplines. In the present paper, we study the potential of deep text-to-3D models in the engineering domain and focus on the chances and challenges when integrating and interacting with 3D assets in computational simula...
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Ahmed Sadik, Sebastian Brulin, Markus Olhofer , "Preprint - CODING BY DESIGN: GPT-4 EMPOWERS AGILE MODEL DRIVEN DEVELOPMENT", arxiv, 2023.
AbstractGenerating code from a natural language using Large Language Models (LLMs) such as ChatGPT, seems groundbreaking. Yet, with more extensive use, it's evident that this approach has its own limitations. The inherent ambiguity of natural language presents challenges for complex software designs. Accordingly, our research offers an Agile Model-Driven Development (MDD) approach that enhances code auto-generation using OpenAI's GPT-4. Our work emphasiz...
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Sebastian Brulin, Mariusz Bujny, Tim Puphal, Stefan Menzel , "Data-driven Evolutionary Optimization of eVTOL Design Concepts based on Multi-agent Simulations", American Institute of Aeronautics and Astronautics SciTech Forum, 2023.
AbstractElectric vertical take-off and landing (eVTOL) aircraft design concepts are currently developed by many companies and research consortia. A relevant topic in the design process is very early on the optimal vehicle specification to maximize the operational profit of the fleet. This paper proposes a novel method that combines open vehicle design concepts with an Evolutionary Algorithm optimization scheme to find the optimal aircraft specifications,...
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Tim Puphal , "Improved Behavior Planning with Cooperation and Group-awareness", IEEE International Conference on Intelligent Transportation Systems, 2023.
AbstractInvited talk about Risk Maps planning in the workshop "Probabilistic Prediction and Comprehensible Motion Planning for Automated Vehicles – Approaches and Benchmarking" at the International Conference on Intelligent Transportation Systems (ITSC 2023). Recent works of intelligent planning, especially how to improve behavior planning with cooperation and group-awareness were presented. You can find more information about the workshop here: https:...
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Hua-Ming Huang, Elena Raponi, Fabian Duddeck, Stefan Menzel, Mariusz Bujny , "Topology Optimization of Periodic Structures for Crash and Static Load Cases using the Evolutionary Level Set Method", Optimization and Engineering, 2023.
AbstractAssembly complexity and manufacturing costs of engineering structures can be significantly reduced by using periodic mechanical components, which are defined by combining multiple identical unit cells into a global topology. Additionally, the superior energy-absorbing properties of lattice-based periodic structures can potentially enhance the overall performance in crash-related applications. Recent research developments in periodic topology opti...
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Nico Andreas Steinhardt, Raphael Wenzel, Malte Probst , Markus Amann , "Lateral Model Predictive Control for Autonomous Vehicle Prototypes", IFAC World Congress 2023, 2023.
AbstractThis paper shows a (lateral) Model Predictive Control (MPC) implementation on an Autonomous Driving (AD) prototype. Rapid prototyping and testing of AD functions in a realistic environment is a crucial step to understanding the advantages and shortcomings of algorithms in research and development of AD. Prototype vehicles show a specific set of requirements which differ from the control deployed in the final products. Vehicles are equipped with s...
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Radu Stoican, Angelo Cangelosi, Thomas H Weisswange , "MEWA: A Benchmark For Meta-Learning in Collaborative Working Agents", IEEE Symposium Series on Computational Intelligence (SSCI 2023), 2023.
AbstractMeta-reinforcement learning aims to overcome important limitations in reinforcement learning, like low sample efficiency and poor generalization, by creating agents that adapt to new tasks. The development of intelligent robots would benefit from such agents. Long-standing issues like data collection and generalization to real-world dynamic environments could be mitigated by sample-efficient adaptable algorithms. However, most such algorithms ...
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Frank Joublin and Antonello Ceravola , "CoPAL: Corrective Planning of Robot Actions with Large Language Models", Artificial Intelligence Meetup Frankfurt, 2023.
AbstractIntroduction of HRI-EU at AI Meetup Frankfurt and presentation of the research done on a robotic system using Large Language Models (LLMs) for task and motion planning. The architecture combines reasoning, planning, and motion, with a special focus on correcting plan errors. Its efficiency is tested in simulations and real-world tasks for tasks like block arrangement, cocktail and pizza preparation....
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