Below you can find a selection of the CCS members' former research projects. Follow the links for more details, demos and related papers.

Interested in our current projects? View them here

The Adaptive Mind

The Universities of Giessen, Marburg, and Darmstadt together with the University of Frankfurt and the Frankfurt Institute for Advanced Studies (FIAS) aim to strategically strengthen research in the field of Mind, Brain, and Behavior. The goal is to observe empirically, describe quantitatively, and model computationally how the human mind continually adapts in an ever-changing and often unpredictable world.
This research project was funded by Hessen State Ministry for Higher Education, Research and the Arts. Building on this project a new Cluster of Excellence with the same name was started in January 2026.

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3AI – The Third Wave of Artificial Intelligence

3AI – The Third Wave of Artificial Intelligence aims to explore the Third Wave of Artificial Intelligence: AI systems should acquire human-like communication and reasoning capabilities and be able to recognize, classify and adapt to new situations autonomously. The goal is not to replace human intelligence, but to extend it reliably and for the benefit of society in an increasingly complex world.
3AI is a collaborative endeavour of the Universities of Darmstadt, Frankfurt, Mainz and the Frankfurt Institute for Advanced Studies (FIAS).
This research project was funded by Hessen State Ministry for Higher Education, Research and the Arts.

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KompAKI

The joint project “KompAKI – Kompetenzzentrum für Arbeit und Künstliche Intelligenz” (Competence Center for Work and Artificial Intelligence) will tap into new potential for human-centric AI applications and their business models, develop new approaches to cooperative AI that enable users to use AI more transparently and easily, and develop new methods for evaluating work in AI-based work systems.
This research project was funded by the German Ministry of Education and Research (BMBF).

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IKIDA

The overall technical and scientific goal of IKIDA is the development of interactive, probabilistic AI algorithms, which benefit from direct interaction with users. Enabling such direct interaction between AI algorithms and users is also intended to lower application hurdles of AI solutions and can potentially increase their sustainability and acceptance. For the development of the AI algorithms we particularly plan to incorporate and develop new cognitive models for human-AI interaction.
This research project was funded by the German Federal Ministry of Research, Technology and Space (BMFTR) (during project period: German Ministry of Education and Research (BMBF)).

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Understanding decision criterion learning

This project conducts behavioral and neurophysiological experiments to achieve a deeper understanding of adaptive choice algorithms and their neural implementation.
This research project was funded by DFG – Deutsche Forschungsgemeinschaft (German Research Foundation).

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PlexPlain – Explaining AI

PlexPlain („Erklärende KI für Komplexe Lineare Programme am Beispiel intelligenter Energiesysteme”) aims at the automated generation of explanations for complex linear programs with a focus on applications in the energy sector.
This research project was funded by the German Federal Ministry of Education and Research (BMBF).

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Active Vision

This project aims at experimentally investigating and quantifying human behavior in sequential tasks that require human subjects to detect spatial or temporal visual targets.
This research project was funded by DFG – Deutsche Forschungsgemeinschaft (German Research Foundation).

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Moral Choice Machine

There is a broad consensus, that the impact of artificial intelligence (AI) on society is likely to further increase. AI systems are not neutral with respect to purpose and society. Ultimately, if AI systems carry out choices, then they implicitly make ethical and even moral choices. How do we equip machines with the ability to learn about ethical or even moral choices?

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KoBo34 – Intuitive HRI

KoBo34 („KoBo34 – Intuitive Interaktion mit kooperativen Assistenzrobotern für das 3. und 4. Lebensalter“) aimed at improving social participation and maintaining personal independence of elderly people by developing an assistive humanoid robot.
This research project was funded by the German Federal Ministry of Education and Research (BMBF).

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DeepSpaceBIM – AI @ Construction Sites

“DeepSpaceBIM 4.1 – Digitaler Bauassistent der Zukunft” aimed at creating a "digital construction assistant" in the form of an experimental development with the overall aim to make the complexity of large-scale construction projects more manageable. To this end it exploited modern information technologies like AR – Augmented Reality, BIM – Building Information Modeling, mobile point cloud capturing, and AI – Artificial Intelligence.
This research project was funded by the German Federal Ministry of Transport and Digital Infrastructure (BMVI).

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Bioinspired Hopping

The legged locomotion found in humans and animals are energetic, versatile, and robust against perturbations. The functionality of the leg can be separated into three locomotor sub-functions which are stance (axial leg function), swing (rotational leg function), and balance (trunk posture control). The stance sub-function is to support body weight and create the center of mass bouncing behavior (e.g. during walking, running, etc.).
This research project was partially funded by DFG – Deutsche Forschungsgemeinschaft (German Research Foundation).

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Human Gait Control

A gait model capable of generating human-like walking behavior at both the kinematic and the muscular level provides a powerful framework for developing state-of-the-art control schemes for humanoids and wearable robots (e.g. exoskeletons, prostheses). “Human Gait Control” aims at demonstrating the feasibility of using a deep reinforcement learning based approach to derive the required sensory-motor mappings to generate human-like locomotion behaviors.
This research project was partially funded by DFG – Deutsche Forschungsgemeinschaft (German Research Foundation).

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SKILLS4ROBOTS – Policy Learning of Motor Skills for Humanoid Robots

The goal of SKILLS4ROBOTS was to develop a autonomous skill learning system that enables humanoid robots to acquire and improve a rich set of motor skills. This robot skill learning system allows scaling of motor abilities up to fully anthropomorphic robots while overcoming the current limitations of skill learning systems to only few degrees of freedom.

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