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jobs [2014/07/11 11:50] – [Theses and Jobs] jworch | jobs [2016/03/03 07:52] – [Theses and Jobs] ahaidu | ||
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If you are looking for a bachelor/ | If you are looking for a bachelor/ | ||
+ | == Lisp / CRAM support assistant (HiWi) == | ||
+ | Technical support for the group for Lisp and the CRAM framework. \\ | ||
+ | 5 hours per week for up to 1 year (paid). | ||
- | == GPU-based Parallelization of Numerical Optimization Techniques (BA/ | + | Requirements: |
+ | * Good programming skills in Common Lisp | ||
+ | * Basic ROS knowledge | ||
- | In the field of Machine Learning, numerical optimization techniques play a focal role. However, as models grow larger, traditional implementations on single-core CPUs suffer from sequential execution causing a severe slow-down. In this thesis, state-of-the-art GPU frameworks | + | The student will be introduced to the CRAM framework at the beginning |
+ | |||
+ | Contact: [[team: | ||
+ | |||
+ | |||
+ | == Integrating PR2 in the Unreal Game Engine Framework | ||
+ | {{ : | ||
+ | |||
+ | Integrating the [[https:// | ||
Requirements: | Requirements: | ||
- | | + | * Good programming skills in C/C++ |
- | | + | * Basic physics/ |
+ | * Basic ROS knowledge | ||
+ | * UE4 basic tutorials | ||
- | Contact: [[team:daniel_nyga|Daniel Nyga]] | + | Contact: [[team:andrei_haidu|Andrei Haidu]] |
- | == Online Learning of Markov Logic Networks for Natural-Language Understanding | + | == Kitchen Activity Games in a Realistic Robotic Simulator |
+ | {{ : | ||
- | Markov Logic Networks (MLNs) combine the expressive power of first-order logic and probabilistic graphical models. In the past, they have been successfully applied to the problem of semantically interpreting and completing natural-language instructions from the web. State-of-the-art learning techniques mostly operate in batch mode, i.e. all training instances need to be known in the beginning of the learning process. In context of this thesis, online learning methods for MLNs are to be investigated, which allow incremental learning, when new examples come in one-by-one. | + | Developing new activities |
Requirements: | Requirements: | ||
- | * Experience | + | * Good programming skills |
- | * Experience with statistical relational learning (e.g. MLNs) is helpful. | + | * Basic physics/ |
- | * Good programming skills in Python. | + | * Gazebo simulator basic tutorials |
- | Contact: [[team:daniel_nyga|Daniel Nyga]] | + | Contact: [[team:andrei_haidu|Andrei Haidu]] |
- | ==HiWi-Position: | ||
- | In the context of the European research project RoboHow.Cog [1,2] we | ||
- | are investigating methods for combining multimodal sources of knowledge (e.g. video, natural-language recipes or computer games), in order to enable mobile robots to autonomously acquire new high level skills like cooking meals or straightening up rooms. | ||
- | The Institute for Artificial Intelligence is hiring a student researcher for the | + | == Automated sensor calibration toolkit (BA/MA)== |
- | development and the integration of probabilistic methods in AI, which enable intelligent robots to understand, interpret and execute natural-language instructions from recipes from the World Wide Web. | + | |
- | This HiWi-Position can serve as a starting point for future Bachelor' | + | Computer vision is an important part of autonomous robots. For robots the image sensors are the main source of information of the surrounding world. Each camera is different, even if they are from the same production line. For computer vision, especially |
- | Tasks: | + | The topic for this thesis is to develop |
- | * Implementation of an interface to the Robot Operating System (ROS). | + | |
- | * Linkage of the knowledge base to the executive of the robot. | + | |
- | * Support | + | |
- | Requirements: | + | {{ : |
- | * Studies in Computer Science (Bachelor' | + | The system should: |
- | * Basic skills in Artificial Intelligence | + | * be independent of the camera type |
- | * Optional: basic skills in Probability Theory | + | * estimate intrinsic and extrinsic parameters |
- | * Optional: basic skills in Machine Learning | + | * calibrate depth images (case of RGB-D) |
- | * Good programming skills in Python and Java | + | * integrate capabilities from Halcon [1] |
+ | * operate autonomously | ||
- | Hours: 10-20 h/week | + | Requirements: |
+ | * Good programming skills in Python and C/C++ | ||
+ | * ROS, OpenCV | ||
- | Contact: | + | [1] http:// |
- | [1] www.robohow.eu\\ | + | Contact: |
- | [2] http:// | + | |
+ | == On-the-fly 3D CAD model creation (MA)== | ||
- | == Depth-Adaptive Superpixels (BA/MA)== | + | Create models during runtime for unknown textured objets based on depth and color information. Track the object and update the model with more detailed information, |
- | {{ : | + | |
- | We are currently investigating a new set of sensors (RGB-D-T), which is a combination of a kinect | + | |
- | Since the current implementation of DASP is not very performant for high resolution images, there are several options for doing a project | + | Requirements: |
+ | * Good programming skills in C/C++ | ||
+ | * strong background | ||
+ | * ROS, OpenCV, PCL | ||
- | Requirements: | + | Contact: [[team: |
- | * Basic knowledge of image processing | + | |
- | * Good programming skills in C/C++. | + | |
- | * Experience with CUDA is helpful | + | |
- | Contact: [[team: | + | == Simulation of a robots belief state to support perception(MA) == |
+ | Create a simulation environment that represents the robots current belief state and can be updated frequently. Use off-screen rendering to investigate the affordances these objects possess, in order to support segmentation, | ||
- | == Depth-Adaptive Superpixels (BA/MA)== | + | Requirements: |
- | {{ : | + | * Good programming skills in C/C++ |
+ | * strong background in computer vision | ||
+ | * Gazebo, OpenCV, PCL | ||
- | For tracking people, the use of particle filters is a common approach. However, the quality of those filters heavily depends on the way particles are spread. In this thesis, a library for the physical simulation of a human model is to be implemented. | + | Contact: [[team: |
- | Requirements: | + | == Multi-expert segmentation of cluttered and occluded scenes == |
+ | |||
+ | Objects in a human environment are usually found in challenging scenes. They can be stacked upon eachother, touching or occluding, can be found in drawers, cupboards, refrigerators and so on. A personal robot assistant in order to execute a task, needs to detect these objects and recognize them. In this thesis a multi-modal approach to interpreting cluttered scenes is going to be investigated, | ||
+ | |||
+ | Requirements: | ||
* Good programming skills in C/C++ | * Good programming skills in C/C++ | ||
- | * Optional: Experience | + | * strong background |
+ | * basic knowledge of ROS, OpenCV, PCL | ||
- | Contact: [[team:jan-hendrik_worch|Jan-Hendrik Worch]] | + | Contact: [[team:ferenc_balint-benczedi|Ferenc Balint-Benczedi]] |
Prof. Dr. hc. Michael Beetz PhD
Head of Institute
Contact via
Andrea Cowley
assistant to Prof. Beetz
ai-office@cs.uni-bremen.de
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