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jobs [2015/03/19 12:25] – [Theses and Jobs] balintbe | jobs [2016/03/03 07:57] – [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 (e.g. CUDA) are to be investigated in order implement numerical optimizers that substantially profit from parallel execution. | + | The student will be introduced to the CRAM framework at the beginning |
- | Requirements: | + | Contact: [[team: |
- | * Skills in numerical optimization algorithms | + | |
- | * Good programming skills in Python and C/C++ | + | |
- | Contact: [[team: | ||
- | == Online Learning of Markov Logic Networks for Natural-Language Understanding | + | == Integrating PR2 in the Unreal Game Engine Framework |
+ | {{ : | ||
- | Markov Logic Networks (MLNs) combine | + | Integrating |
Requirements: | Requirements: | ||
- | * Experience | + | * Good programming skills |
- | * Experience with statistical relational learning (e.g. MLNs) is helpful. | + | * Basic physics/ |
- | * Good programming skills in Python. | + | * Basic ROS knowledge |
+ | * UE4 basic tutorials | ||
- | Contact: [[team:daniel_nyga|Daniel Nyga]] | + | Contact: [[team:andrei_haidu|Andrei Haidu]] |
- | ==HiWi-Position: | + | == Realistic Grasping using Unreal Engine |
- | 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 | + | The objective of the project |
- | development and the integration of probabilistic methods | + | ious human-like grasping approaches |
- | This HiWi-Position can serve as a starting point for future Bachelor' | + | The game consist of a household environment where a user has to execute various given tasks, such as cooking |
- | Tasks: | + | In order to improve |
- | * Implementation of an interface | + | be able to switch during runtime |
- | * Linkage | + | grasp, precision grip etc.) he/she would like to use. |
- | | + | |
- | + | Requirements: | |
- | Requirements: | + | * Good programming |
- | * Studies in Computer Science (Bachelor' | + | * Good knowledge of the Unreal Engine API. |
- | * Basic skills in Artificial Intelligence | + | * Experience with skeletal control / animations / 3D models |
- | * Optional: basic skills in Probability Theory | + | |
- | * Optional: basic skills | + | |
- | * Good programming skills in Python and Java | + | |
- | + | ||
- | Hours: 10-20 h/week | + | |
- | + | ||
- | Contact: [[team: | + | |
- | [1] www.robohow.eu\\ | ||
- | [2] http:// | ||
+ | Contact: [[team/ | ||
- | == Kitchen Activity Games in a Realistic Robotic Simulator (BA/MA/HiWi)== | + | == Kitchen Activity Games in a Realistic Robotic Simulator (BA/MA)== |
{{ : | {{ : | ||
Line 69: | Line 64: | ||
Contact: [[team: | Contact: [[team: | ||
- | == Integrating Eye Tracking in the Kitchen Activity Games (BA/MA)== | ||
- | {{ : | ||
- | Integrating the eye tracker in the [[http:// | ||
- | Requirements: | ||
- | * Good programming skills in C/C++ | ||
- | * Gazebo simulator basic tutorials | ||
- | Contact: [[team: | + | == Automated sensor calibration toolkit (BA/MA)== |
- | == Hand Skeleton Tracking Using Two Leap Motion Devices (BA/MA)== | + | 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 for robots manipulating their environment, |
- | {{ : | + | |
- | Improving the skeletal tracking offered by the [[https:// | + | The topic for this thesis is to develop an automated system for calibrating cameras, especially RGB-D cameras like the Kinect v2. |
- | The tracked hand can then be used as input for the Kitchen Activity Games framework. | + | {{ : |
+ | The system should: | ||
+ | * be independent of the camera type | ||
+ | * estimate intrinsic and extrinsic parameters | ||
+ | * calibrate depth images (case of RGB-D) | ||
+ | * integrate capabilities from Halcon [1] | ||
+ | * operate autonomously | ||
- | Requirements: | + | Requirements: |
- | * Good programming skills in C/C++ | + | * Good programming skills in Python and C/C++ |
+ | * ROS, OpenCV | ||
- | Contact: | + | [1] http:// |
- | == Fluid Simulation in Gazebo (BA/MA)== | + | Contact: [[team:alexis_maldonado|Alexis Maldonado]] and [[team: |
- | | + | |
- | [[http:// | + | == On-the-fly 3D CAD model creation |
- | Currently there is an [[http:// | + | 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, |
- | The computational method for the fluid simulation is SPH (Smoothed-particle Dynamics), however newer and better methods based on SPH are currently present | + | Requirements: |
- | and should be implemented (PCISPH/IISPH). | + | * Good programming skills in C/C++ |
+ | * strong background in computer vision | ||
+ | * ROS, OpenCV, PCL | ||
- | The interaction between the fluid and the rigid objects is a naive one, the forces and torques are applied only from the particle collisions (not taking into account pressure and other forces). | + | Contact: [[team: |
- | Another topic would be the visualization | + | == Simulation |
- | Here is a [[https:// | + | Create |
- | Requirements: | + | Requirements: |
* Good programming skills in C/C++ | * Good programming skills in C/C++ | ||
- | * Interest | + | * strong background |
- | * Basic physics/ | + | * Gazebo, OpenCV, PCL |
- | * Gazebo | + | |
- | Contact: [[team:andrei_haidu|Andrei Haidu]] | + | Contact: [[team:ferenc_balint-benczedi|Ferenc Balint-Benczedi]] |
+ | == Multi-expert segmentation of cluttered and occluded scenes == | ||
- | == Automated sensor calibration toolkit (MA)== | + | 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, |
- | Computer | + | Requirements: |
+ | * Good programming skills in C/C++ | ||
+ | * strong background in 3D vision | ||
+ | * basic knowledge | ||
- | The topic for this master thesis is to develop an automated system for calibrating cameras, especially RGB-D cameras like the Kinect v2. | + | Contact: [[team: |
- | The system should be: | ||
- | * independent of the camera type | ||
- | * estimate intrinsics and extrinsics | ||
- | * have depth calibration (case of RGBD) | ||
- | * integrate capabilities from Halcon [1] | ||
- | Requirements: | ||
- | * Good programming skills in Python and C/C++ | ||
- | * ROS, OpenCV | ||
- | |||
- | [1] http:// | ||
- | |||
- | Contact: [[team: |
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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