Research in Artificial Intelligence for Autonomous Mobile Robots

The Institute for Artificial Intelligence (IAI) at the University of Bremen, Germany, headed by Prof. Michael Beetz, investigates methods for cognition-enabled robot control. The research is at the intersection of robotics and Artificial Intelligence (AI) and includes methods for intelligent perception, dexterous object manipulation, plan-based robot control and knowledge representation for robots. Robots performing complex tasks in open domains, such as assisting humans in a household or collaboratively assembling products in a factory, need to have cognitive capabilities for interpreting their sensor data, understanding scenes, selecting and parameterizing their actions, recognizing and handling failures and interacting with humans. IAI develops solutions for these kinds of issues, implements and test them on the robots in our laboratory. A particular focus of the group is on the integration of individual methods into complete cognition-enabled robot control systems and the release of the developed software as open-source libraries.

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  • c++
  • python
  • ros
  • unreal engine
  • lisp


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Institute for Artificial Intelligence 2018 Projects

  • Mircea-Tudor Chifor
    Eye Tracking GUI Integration
    My proposed Project consists of developing a GUI with Unreal Engine for Eye Tracking and any adjacent work involving the aforementioned tehnology.
  • An T. Le
    Flexible perception pipeline manipulation for RoboSherlock
    The project proposes flexible pipeline handling mechanism for RoboSherlock framework. The current state of RoboSherlock implementation does not allow...
  • Shingo Kitagawa
    Implementation of Deep Learning Annotators written in Python into RoboSherlock
    In GSoC, I propose to introduce deep learning annotators in RoboSherlock for more various task. Because many deep learning frameworks and...
  • Bj√∂rn Veit
    KnowRob visualization in RobCoG
    The RobCoG project is presenting a new perspective on how robots are supposed to learn everyday tasks. Learning from humans essentially playing a...
  • Kaivalya Rawal
    Markov Logic Networks in Python: PracMLN
    Markov Logic Networks (MLNs) are a generalisation of first-order logic and probabilistic graphical models, thus forming a powerful mechanism of...
  • Shixin Li
    Proposal for RoboSherlock GSOC 18
    This project targets at enabling the current RoboSherlock to work in form of parallel pipeline, which also includes merging results of different...