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jobs [2014/06/11 11:09] – [Theses and Jobs] jworch | jobs [2017/05/03 12:37] – gkazhoya | ||
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+ | == Lisp / CRAM support assistant (HiWi) == | ||
- | == GPU-based Parallelization of Numerical Optimization Techniques (BA/ | + | Technical support for the group for Lisp and the CRAM framework. \\ |
- | + | Ca. 10 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: | ||
- | * Experience in Machine Learning. | ||
- | * Experience with statistical relational learning (e.g. MLNs) is helpful. | ||
- | * Good programming skills in Python. | ||
- | Contact: [[team:daniel_nyga|Daniel Nyga]] | + | == Integrating PR2 in the Unreal Game Engine Framework (BA)== |
+ | | ||
- | + | Integrating the [[https://www.willowgarage.com/ | |
- | ==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/HiWi)== | + | 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/ | ||
- | == Tools for knowledge acquisition from the Web (BA/MA/HiWi) == | + | == Kitchen Activity Games in a Realistic Robotic Simulator |
+ | {{ : | ||
- | There are several options for doing a project related to the acquisition of | + | Developing new activities and improving the current simulation framework done under the [[http:// |
- | knowledge from Web sources like online shops, repositories of object models, | + | |
- | recipe databases, etc. | + | |
Requirements: | Requirements: | ||
- | * Programing | + | * Good programming |
- | * Experience with Web languages and datamining techniques is helpful | + | * Basic physics/ |
- | * Depending on the focus of the project, experience with database technology, natural-language processing or computer vision may be helpful | + | * Gazebo simulator basic tutorials |
- | + | ||
- | Contact: [[team: | + | |
+ | Contact: [[team: |
Prof. Dr. hc. Michael Beetz PhD
Head of Institute
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Andrea Cowley
assistant to Prof. Beetz
ai-office@cs.uni-bremen.de
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