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

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?
Ongoing research interest.

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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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