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jobs [2014/08/29 09:33] – [Theses and Jobs] ahaidu | jobs [2017/02/02 11:46] – [Theses and Jobs] balintbe | ||
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If you are looking for a bachelor/ | If you are looking for a bachelor/ | ||
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+ | == Lisp / CRAM support assistant (HiWi) == | ||
- | + | Technical support for the group for Lisp and the CRAM framework. \\ | |
- | == GPU-based Parallelization of Numerical Optimization Techniques (BA/ | + | 5 hours per week for up to 1 year (paid). |
- | + | ||
- | 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 | + | |
Requirements: | Requirements: | ||
- | * Skills | + | * Good programming skills |
- | * Good programming skills in Python and C/C++ | + | * Basic ROS knowledge |
- | Contact: [[team: | + | 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. |
- | == Online Learning of Markov Logic Networks for Natural-Language Understanding (MA)== | + | Contact: [[team: |
+ | --> | ||
+ | </ | ||
- | 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: | + | == Integrating PR2 in the Unreal Game Engine Framework |
- | * Experience | + | {{ : |
- | * Experience with statistical relational learning | + | |
- | * Good programming skills in Python. | + | |
- | Contact: | + | Integrating the [[https:// |
- | + | ||
- | + | ||
- | ==HiWi-Position: Knowledge Representation & Language Understanding for Intelligent Robots== | + | |
- | + | ||
- | 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), | + | |
- | + | ||
- | The Institute for Artificial Intelligence is hiring a student researcher for the | + | |
- | 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' | + | |
- | + | ||
- | Tasks: | + | |
- | * Implementation of an interface to the Robot Operating System (ROS). | + | |
- | * 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 physics/ |
- | * Optional: basic skills in Probability Theory | + | * Basic ROS knowledge |
- | * Optional: | + | * UE4 basic tutorials |
- | * Good programming skills in Python and Java | + | |
- | Hours: 10-20 h/week | + | Contact: [[team: |
- | Contact: [[team: | ||
- | [1] www.robohow.eu\\ | + | == Realistic Grasping using Unreal Engine (BA/MA) == |
- | [2] http:// | + | |
+ | {{ : | ||
- | == Depth-Adaptive Superpixels (BA/MA)== | + | The objective of the project is to implement var- |
- | {{ : | + | ious human-like grasping approaches in a game developed using [[https:// |
- | We are currently investigating a new set of sensors (RGB-D-T), which is a combination of a kinect with a thermal image camera. Within this project we want to enhance the Depth-Adaptive Superpixels (DASP) to make use of the thermal sensor data. Depth-Adaptive Superpixels oversegment an image taking into account the depth value of each pixel. | + | |
- | Since the current implementation | + | The game consist |
- | Requirements: | + | In order to improve the ease of manipulating objects the user should |
- | * Basic knowledge of image processing | + | be able to switch during runtime the type of grasp (pinch, power |
- | * Good programming skills in C/C++. | + | grasp, precision grip etc.) he/she would like to use. |
- | * Experience with CUDA is helpful | + | |
+ | Requirements: | ||
+ | * Good programming skills in C++ | ||
+ | * Good knowledge of the Unreal Engine API. | ||
+ | * Experience with skeletal control / animations / 3D models in Unreal Engine. | ||
- | Contact: [[team: | ||
+ | Contact: [[team/ | ||
- | == Physical Simulation of Humans (BA/MA)== | + | == Kitchen Activity Games in a Realistic Robotic Simulator (BA/MA)== |
- | {{ : | + | |
- | + | ||
- | 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. | + | |
- | + | ||
- | Requirements: | + | |
- | * Good programming skills in C/C++ | + | |
- | * Optional: Experience in working with physics libraries such as Bullet | + | |
- | + | ||
- | Contact: [[team: | + | |
- | + | ||
- | == Kitchen Activity Games in a Realistic Robotic Simulator (BA/MA/HiWi)== | + | |
{{ : | {{ : | ||
- | Developing new activities and improving the current simulation framework done under the Gazebo robotic simulator. Creating a custom GUI for the game, in order to launch new scenarios, save logs etc. | + | Developing new activities and improving the current simulation framework done under the [[http:// |
Requirements: | Requirements: | ||
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* Basic physics/ | * Basic physics/ | ||
* Gazebo simulator basic tutorials | * Gazebo simulator basic tutorials | ||
- | |||
- | Contact: [[team: | ||
- | |||
- | == Integrating Eye Tracking in the Kitchen Activity Games (BA/MA)== | ||
- | {{ : | ||
- | |||
- | Integrating the eye tracker in the Gazebo based Kitchen Activity Games framework | ||
- | and logging the gaze of the user during the gameplay. From the information typical activities should be inferred. | ||
- | |||
- | Requirements: | ||
- | * Good programming skills in C/C++ | ||
- | * Gazebo simulator basic tutorials | ||
- | |||
- | Contact: [[team: | ||
- | |||
- | == Hand Skeleton Tracking Using Two Leap Motion Devices (BA/MA)== | ||
- | {{ : | ||
- | |||
- | Improving the skeletal tracking offered by the 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. | ||
- | |||
- | The tracked hand can then be used as input for the Kitchen Activity Games framework. | ||
- | |||
- | Requirements: | ||
- | * Good programming skills in C/C++ | ||
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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