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jobs [2015/07/28 12:11] – [Theses and Jobs] winkler | jobs [2018/01/22 09:23] – [Theses and Student Jobs] ahaidu | ||
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~~NOTOC~~ | ~~NOTOC~~ | ||
- | =====Theses and Jobs===== | ||
- | If you are looking for a bachelor/ | ||
+ | =====Open researcher positions===== | ||
+ | == Researcher in the area of Knowledge bases and knowledge acquisition == | ||
- | == GPU-based Parallelization of Numerical Optimization Techniques (BA/MA/HiWi)== | + | Position code A132/17. Please see [[http:// |
- | 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. | ||
- | Requirements: | + | == Researcher with background |
- | * Skills | + | |
- | * Good programming | + | |
- | Contact: | + | Position code A133/17. Please see [[http:// |
- | == Online Learning of Markov Logic Networks for Natural-Language Understanding (MA)== | ||
- | 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, | ||
- | Requirements: | ||
- | * Experience in Machine Learning. | ||
- | * Experience with statistical relational learning (e.g. MLNs) is helpful. | ||
- | * Good programming skills in Python. | ||
- | Contact: [[team: | ||
- | ==HiWi-Position: | + | =====Theses and Student Jobs===== |
+ | If you are looking for a bachelor/ | ||
- | In the context of the European research project RoboHow.Cog [1,2] we | + | < |
- | are investigating methods for combining multimodal sources of knowledge | + | == Lisp / CRAM support assistant |
- | The Institute | + | Technical support |
- | development | + | 8+ hours per week for up to 1 year (paid). |
- | + | ||
- | This HiWi-Position can serve as a starting point for future Bachelor' | + | |
- | + | ||
- | Tasks: | + | |
- | * Implementation of an interface | + | |
- | * Linkage of the knowledge base to the executive of the robot. | + | |
- | * Support for the scientific staff in extending and integrating components onto the robot platform PR2. | + | |
Requirements: | Requirements: | ||
- | * Studies | + | * Good programming skills |
- | * Basic skills in Artificial Intelligence | + | * Basic ROS knowledge |
- | * Optional: basic skills in Probability Theory | + | |
- | * Optional: basic skills in Machine Learning | + | |
- | * Good programming skills in Python and Java | + | |
- | Hours: 10-20 h/week | + | The student will be introduced to the CRAM framework at the beginning of the job, which is a robot programming framework written in Lisp. The student will then be responsible for assisting not familiar with the framework people, explaining them the parts they don't understand and pointing them to the relevant documentation sources. |
- | Contact: [[team:daniel_nyga|Daniel Nyga]] | + | Contact: [[team:gayane_kazhoyan|Gayane Kazhoyan]] |
+ | --></ | ||
- | [1] www.robohow.eu\\ | + | == 3D Model / Material |
- | [2] http://www.youtube.com/watch?v=0eIryyzlRwA | + | {{ : |
+ | Developing and improving 3D Models in Blender / Maya. Importing the models in Unreal Engine, where the Materials and Lightning should be improved to be close as possible to realism. | ||
- | == Kitchen Activity Games in a Realistic Robotic Simulator (BA/ | + | Bonus: Working with state of the art 3D Scanners |
- | | + | |
- | + | ||
- | Developing new activities and improving the current simulation framework done under the [[http://gazebosim.org/|Gazebo]] robotic simulator. Creating a custom GUI for the game, in order to launch | + | |
Requirements: | Requirements: | ||
- | * Good programming skills in C/C++ | + | * Experience with Blender |
- | * Basic physics/rendering engine knowledge | + | * Knowledge of Unreal Engine material |
- | * Gazebo simulator basic tutorials | + | |
- | 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: | Contact: [[team: | ||
- | == Hand Skeleton Tracking Using Two Leap Motion Devices | + | == Unreal Engine Editor |
- | {{ :research:leap_motion.jpg? | + | {{ :research:unreal_editor.png? |
- | Improving the skeletal tracking offered by the [[https://developer.leapmotion.com/|Leap Motion SDK]], by using two devices (one tracking vertically the other horizontally) and switching between them to the one that has the best current view of the hand. | + | Creating user interfaces (panel customization) for various internal plugins using the Unreal C++ framework |
- | The tracked hand can then be used as input for the Kitchen Activity Games framework. | ||
Requirements: | Requirements: | ||
- | * Good programming skills in C/C++ | + | * Good C++ programming skills |
+ | * Familiar with [[https:// | ||
+ | * Familiar with Unreal Engine API | ||
Contact: [[team: | Contact: [[team: | ||
- | == Fluid Simulation | + | == Integrating PR2 in the Unreal Game Engine Framework |
- | {{ :research:fluid.png?200|}} | + | {{ :research:unreal_ros_pr2.png?100|}} |
- | + | ||
- | [[http:// | + | |
- | + | ||
- | Currently there is an [[http:// | + | |
- | + | ||
- | The computational method for the fluid simulation is SPH (Smoothed-particle Dynamics), however newer and better methods based on SPH are currently present | + | |
- | and should be implemented (PCISPH/ | + | |
- | + | ||
- | 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). | + | |
- | + | ||
- | Another topic would be the visualization of the fluid, currently is done by rendering every particle. For the rendering engine [[http:// | + | |
- | Here is a [[https://vimeo.com/104629835|video]] example of the current state of the fluid in Gazebo. | + | Integrating the [[https://www.willowgarage.com/pages/ |
Requirements: | Requirements: | ||
* Good programming skills in C/C++ | * Good programming skills in C/C++ | ||
- | * Interest in Fluid simulation | ||
* Basic physics/ | * Basic physics/ | ||
- | * Gazebo simulator and Fluidix | + | * Basic ROS knowledge |
+ | * UE4 basic tutorials | ||
Contact: [[team: | Contact: [[team: | ||
- | == Automated sensor calibration toolkit | + | == Realistic Grasping using Unreal Engine |
- | 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, | + | {{ : |
- | The topic for this thesis | + | The objective of the project |
+ | ious human-like grasping approaches in a game developed using [[https:// | ||
- | {{ : | + | The game consist |
- | The system should: | + | |
- | * be independent | + | |
- | * estimate intrinsic and extrinsic parameters | + | |
- | * calibrate depth images (case of RGB-D) | + | |
- | * integrate capabilities from Halcon [1] | + | |
- | * operate autonomously | + | |
+ | In order to improve the ease of manipulating objects the user should | ||
+ | be able to switch during runtime the type of grasp (pinch, power | ||
+ | grasp, precision grip etc.) he/she would like to use. | ||
+ | | ||
Requirements: | Requirements: | ||
- | * Good programming skills in Python and C/C++ | + | * Good programming skills in C++ |
- | * ROS, OpenCV | + | * Good knowledge of the Unreal Engine API. |
+ | * Experience with skeletal control / animations / 3D models in Unreal Engine. | ||
- | [1] http:// | ||
- | |||
- | Contact: [[team: | ||
- | |||
- | == On-the-fly 3D CAD model creation (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, | ||
- | |||
- | Requirements: | ||
- | * Good programming skills in C/C++ | ||
- | * strong background in computer vision | ||
- | * ROS, OpenCV, PCL | ||
- | |||
- | 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, | ||
- | |||
- | Requirements: | ||
- | * Good programming skills in C/C++ | ||
- | * strong background in computer vision | ||
- | * Gazebo, OpenCV, PCL | ||
- | |||
- | Contact: [[team: | ||
- | |||
- | == 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++ | ||
- | * strong background in 3D vision | ||
- | * basic knowledge of ROS, OpenCV, PCL | ||
- | Contact: [[team: | + | 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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