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

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

© Bielefeld University/Patrick Pollmeier

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
© University of Bremen/Patrick Pollmeier
» learn about the ViB

News & Events

Katharina Rohlfing and Britta Wrede (left to right)
© Susanne Freitag / Michael Adamski

Building trust in science for UNESCO World Science Day

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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

 

The effect of data poisoning on counterfactual explanations (2026)

Authors: André Artelt, Shubham Sharma, Freddy Lecué, Barbara Hammer
Published at: Information Fusion (Volume: 132)
10.1016/j.inffus.2026.104237

Breaking through data scarcity: A novel diffusion model approach for snoring sound augmentation and classification (2026)

Authors: Tianrui Jia, Haojie Zhang, Hanhan Wu, Qiyang Sun, Xin Jing, Boyang Meng, Lin Shen, Liang Wang, Kun Qian, Ye Zhang, Bin Hu, Tanja Schultz, Björn W. Schuller, Yoshiharu Yamamoto
Published at: Biomedical Signal Processing and Control (Volume: 116)
10.1016/j.bspc.2026.109449

A practical guide to streaming continual learning (2026)

Authors: Andrea Cossu, Federico Giannini, Giacomo Ziffer, Alessio Bernardo, Alexander Gepperth, Emanuele Della Valle, Barbara Hammer, Davide Bacciu
Published at: Neurocomputing (Volume: 674)
10.1016/j.neucom.2026.132951

Learning in federated and dynamic environments: A tutorial on challenges, trends, and practical strategies (2026)

Authors: Mirko Polato, Barbara Hammer, Manuel Röder, Frank-Michael Schleif
Published at: Neurocomputing (Volume: 672)
10.1016/j.neucom.2026.132671

Artificial intelligence and infectious diseases: an evidence-driven conceptual framework for research, public health, and clinical practice (2026)

Authors: Anna Odone, Chiara Barbati, Silvia Amadasi, Tanja Schultz, David B Resnik
Published at: Lancet Infectious Diseases (Volume: 26)
10.1016/S1473-3099(25)00412-8

Interpretable event diagnosis in water distribution networks (2026)

Authors: André Artelt, Stelios G. Vrachimis, Demetrios G. Eliades, Ulrike Kuhl, Barbara Hammer, Marios M. Polycarpou
Published at: Intelligent Systems with Applications (Volume: 29)
10.1016/j.iswa.2025.200621

The relation between children's shyness and their contingent dialogical actions when reacting to a social robot's instructions (2026)

Authors: Valeriia Tykhonenko, Nils F. Tolksdorf, Katharina J. Rohlfing
Published at: Philosophical Transactions of the Royal Society of London Series B Biological Sciences (Volume: 381)
10.1098/rstb.2024.0375

Missing Value Imputation With Adversarial Random Forests—MissARF (2026)

Authors: Pegah Golchian, Jan Kapar, David S. Watson, Marvin N. Wright
Published at: Statistics in Medicine (Volume: 45)
10.1002/sim.70379

Giving AI agents a sense of control facilitates reinforcement learning in multitasking scenarios (2026)

Authors: Annika Österdiekhoff, Nils Wendel Heinrich, Nele Russwinkel, Stefan Kopp
Published at: Plos One (Volume: 21)
10.1371/journal.pone.0342305

Spiking neural networks for EEG signal analysis: From theory to practice (2026)

Authors: Siqi Cai, Zheyuan Lin, Xiaoli Liu, Wenjie Wei, Shuai Wang, Malu Zhang, Tanja Schultz, Haizhou Li
Published at: Neural Networks (Volume: 194)
10.1016/j.neunet.2025.108127
» all publications
Philipp Cimiano
© Michael Adamski

Philipp Cimiano

Bielefeld University
CoAI speaker
Michael Beetz
© Institute for Artificial Intelligence, University of Bremen

Michael Beetz

University of Bremen
CoAI speaker
Katharina Rohlfing
© Susanne Freitag

Katharina Rohlfing

Paderborn University
CoAI speaker
» all members