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jobs [2016/03/03 07:52] – [Theses and Jobs] ahaidu | jobs [2017/10/24 07:16] – [Theses and Student Jobs] ahaidu | ||
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- | =====Theses and Jobs===== | + | |
+ | =====Open researcher positions===== | ||
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+ | == Researcher in the area of Knowledge bases and knowledge acquisition == | ||
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+ | Position code A132/17. Please see [[http:// | ||
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+ | == Researcher with background in VR programming == | ||
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+ | Position code A133/17. Please see [[http:// | ||
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+ | =====Theses and Student | ||
If you are looking for a bachelor/ | If you are looking for a bachelor/ | ||
+ | < | ||
== Lisp / CRAM support assistant (HiWi) == | == Lisp / CRAM support assistant (HiWi) == | ||
Technical support for the group for Lisp and the CRAM framework. \\ | Technical support for the group for Lisp and the CRAM framework. \\ | ||
- | 5 hours per week for up to 1 year (paid). | + | 8+ hours per week for up to 1 year (paid). |
Requirements: | Requirements: | ||
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Contact: [[team: | Contact: [[team: | ||
+ | --></ | ||
- | == Integrating PR2 in the Unreal Game Engine Framework (BA)== | + | == Integrating PR2 in the Unreal Game Engine Framework (BA/MA/HiWi)== |
{{ : | {{ : | ||
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Contact: [[team: | Contact: [[team: | ||
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- | == Kitchen Activity Games in a Realistic Robotic Simulator (BA/MA)== | ||
- | {{ : | ||
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- | Developing new activities and improving the current simulation framework done under the [[http:// | ||
- | |||
- | Requirements: | ||
- | * Good programming skills in C/C++ | ||
- | * Basic physics/ | ||
- | * Gazebo simulator basic tutorials | ||
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- | Contact: [[team: | ||
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- | == 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: | + | Contact: [[team/ |
- | == On-the-fly 3D CAD model creation | + | == Kitchen Activity Games in a Realistic Robotic Simulator |
+ | {{ : | ||
- | Create models during runtime for unknown textured objets based on depth and color information. Track the object and update | + | Developing new activities |
- | Requirements: | + | Requirements: |
* Good programming skills in C/C++ | * Good programming skills in C/C++ | ||
- | * strong background in computer vision | + | * Basic physics/rendering |
- | * ROS, OpenCV, PCL | + | * Gazebo |
- | + | ||
- | 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 | + | |
- | + | ||
- | 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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