TIAGo robot helping in kitchen in the Cognitive Service Robotics Apartment lab

Researchers around the world can access our Virtual Research and Training Building.

Breaking new ground in AI-enabled robotics

Our Vision: The Joint Research Center on Cooperative and Cognition-enabled AI (CoAI JRC) is Germany’s leading center for interdisciplinary research and innovation on cooperative and cognition-enabled artificial intelligence that features human-centered, embodied, and real-world agency in the sense that it is capable of acting together with humans in a meaningful and goal-directed manner.

The central hypothesis of CoAI is that AI systems need to be equipped with powerful cognitive, reasoning, communicative and interaction abilities to successfully act in the physical and social world. They have to understand and reason about their own actions and those of others as a basis to provide contextualized support for the wellbeing of humans and society at large.

» about us

Robot arm helping a human with an injured hand

AI that works cooperatively in human physical and social environments

Our Mission: The researchers of CoAI JRC join forces to break new ground in the communication and interaction of humans and robots by developing AI systems that have a deep and actionable understanding of how to perform everyday joint tasks in natural human environments. The AI systems targeted by CoAI are able to successfully act in the physical and social world by adapting and learning new skills through cooperating and communicating with their human partners to eventually become competent and trustworthy partners.

» our objectives

Discover our virtual research and training building

Openness is the most efficient and sustainable approach to successful innovation in our current fast-moving AI research environment. This is why the CoAI Center aims to provide external researchers with convenient access to a Virtual Research and Training Building (ViB), which will enable scientists from anywhere in the world to work as if the are physically present in our labs. In the ViB, members of the international CoAI research community have access to AI-ready digital twin robots, research laboratories, and environments to conduct research in AI-enabled robotics, human-robot interaction, education science and developmental robotics. We also support a variety of open data and open software tools, such as the cognitive robot architecture CRAM.

Operating a digital twin PR2 in a virtual kitchen lab

» learn about the ViB

News & Events

Katharina Rohlfing and Britta Wrede (left to right)

Building trust in science for UNESCO World Science Day

» read more

News

26.01.24

“FAME” Research Initiative by the CoAI JRC’s Michael Beetz will Enable Robots to Visualize Future Actions

An important challenge for cooperative and cognition-enabled robotics is to develop robots that have the ability to consider different possible courses of action and their likely outcomes before selecting one. This is especially important for robots that are engaged in joint tasks with human partners in which the sub-tasks and individual steps have not yet […]

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News

17.01.24

CoAI Virtual Building Featured in Up2Date

The CoAI Virtual Research and Training Building is featured in the latest issue of up2date, the online magazine of the University of Bremen: “Tall windows, a wide, bright hallway, a mirrored elevator: the virtual research building on cognitive-based AI can be entered like a location in a computer game which is waiting to be explored. […]

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15.01.2024, 16:00 - 18:00

Talk by Johanna Seibt on the Problem of Artificial “Social Others”

Title: The Problem of Artificial “Social Others”: How Much Sociality Do We Need for Hybrid Intelligence? Abstract: Co-working, co-creating, cooperation, collaboration—social interactions among humans take many different forms even when the single actions involved are functionally similar: What we take ourselves to be doing together, depends on how we do it together. This raises a […]

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The CoAI JRC Is Part of a Thriving AI Research Ecosystem

The CoAI JRC is embedded in a network of independent projects, research initiatives, and partners in industry and the public sector that collectively form a thriving ecosystem of research in AI and robotics.

Virtual Building

Transfer

Research

Educational Resources

What you need to know about a learning robot: Identifying the enabling architecture of complex systems (2024)

Authors: Helen Beierling, Phillip Richter, Mara Brandt, Lutz Terfloth, Carsten Schulte, Heiko Wersing, Anna-Lisa Vollmer

Published at: Cognitive Systems Research (Volume: 88)

10.1016/j.cogsys.2024.101286

Comparing generative and extractive approaches to information extraction from abstracts describing randomized clinical trials (2024)

Authors: Christian Witte, David M. Schmidt, Philipp Cimiano

Published at: Journal of Biomedical Semantics (Volume: 15)

10.1186/s13326-024-00305-2

Lactation support in neonatal intensive care units in Germany from the mothers’ perspective – a mixed-method study of the current status and needs (2024)

Authors: Isabella Schwab, Ricarda Wullenkord, Friederike Eyssel, Till Dresbach, Nadine Scholten

Published at: BMC Pregnancy and Childbirth (Volume: 24)

10.1186/s12884-024-06339-9

Integrating federated learning for improved counterfactual explanations in clinical decision support systems for sepsis therapy (2024)

Authors: Christoph Düsing, Philipp Cimiano, Sebastian Rehberg, Christiane Scherer, Olaf Kaup, Christiane Köster, Stefan Hellmich, Daniel Herrmann, Kirsten Laura Meier, Simon Claßen, Rainer Borgstedt

Published at: Artificial Intelligence in Medicine (Volume: 157)

10.1016/j.artmed.2024.102982

Enhancing anatomy learning through collaborative VR? An advanced investigation (2024)

Authors: Haya Almaree, Roland Fischer, René Weller, Verena Uslar, Dirk Weyhe, Gabriel Zachmann

Published at: Computers and Graphics (Pergamon) (Volume: 123)

10.1016/j.cag.2024.104019

Feature-based analyses of concept drift (2024)

Authors: Fabian Hinder, Valerie Vaquet, Barbara Hammer

Published at: Neurocomputing (Volume: 600)

10.1016/j.neucom.2024.127968

Energy expenditure prediction in preschool children: a machine learning approach using accelerometry and external validation (2024)

Authors: Hannah J. Coyle-Asbil, Lukas Burk, Mirko Brandes, Berit Brandes, Christoph Buck, Marvin N. Wright, Lori Ann Vallis

Published at: Physiological measurement (Volume: 45)

10.1088/1361-6579/ad7ad2

Polynomial Formal Verification of Arithmetic Circuits (2024)

Authors: Alireza Mahzoon, Rolf Drechsler

Published at: Foundations and Trends in Electronic Design Automation (Volume: 14)

10.1561/1000000059

ReSG: A Data Structure for Verification of Majority-based In-memory Computing on ReRAM Crossbars (2024)

Authors: Kousik Bhunia, Arighna Deb, Kamalika Datta, Muhammad Hassan, Saeideh Shirinzadeh, Rolf Drechsler

Published at: ACM Transactions on Embedded Computing Systems (Volume: 23)

10.1145/3615358

AutoBench: Automatic Testbench Generation and Evaluation Using LLMs for HDL Design (2024)

Authors: Ruidi Qiu, Grace Li Zhang, Rolf Drechsler, Ulf Schlichtmann, Bing Li

Published at: MLCAD 2024 - Proceedings of the 2024 ACM/IEEE International Symposium on Machine Learning for CAD

10.1145/3670474.3685956

» all publications

Breaking new ground in AI-enabled robotics

AI that works cooperatively in human physical and social environments

Discover our virtual research and training building

News & Events

Building trust in science for UNESCO World Science Day

“FAME” Research Initiative by the CoAI JRC’s Michael Beetz will Enable Robots to Visualize Future Actions

CoAI Virtual Building Featured in Up2Date

Talk by Johanna Seibt on the Problem of Artificial “Social Others”

The CoAI JRC Is Part of a Thriving AI Research Ecosystem

What you need to know about a learning robot: Identifying the enabling architecture of complex systems (2024)

Comparing generative and extractive approaches to information extraction from abstracts describing randomized clinical trials (2024)

Lactation support in neonatal intensive care units in Germany from the mothers’ perspective – a mixed-method study of the current status and needs (2024)

Integrating federated learning for improved counterfactual explanations in clinical decision support systems for sepsis therapy (2024)

Enhancing anatomy learning through collaborative VR? An advanced investigation (2024)

Feature-based analyses of concept drift (2024)

Energy expenditure prediction in preschool children: a machine learning approach using accelerometry and external validation (2024)

Polynomial Formal Verification of Arithmetic Circuits (2024)

ReSG: A Data Structure for Verification of Majority-based In-memory Computing on ReRAM Crossbars (2024)

AutoBench: Automatic Testbench Generation and Evaluation Using LLMs for HDL Design (2024)

Philipp Cimiano

Michael Beetz

Katharina Rohlfing