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jobs [2016/02/05 18:23] – [Theses and Jobs] froggy86 | jobs [2017/05/03 12:37] – gkazhoya | ||
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- | == Integrating PR2 in the Unreal Game Engine Framework | + | == Lisp / CRAM support assistant |
- | {{ : | + | |
- | Integrating the [[https:// | + | Technical |
+ | 8-16 hours per week for up to 1 year (paid). | ||
Requirements: | Requirements: | ||
- | * Good programming skills in C/C++ | + | * Good programming skills in Common Lisp |
- | * Basic physics/ | + | |
* Basic ROS knowledge | * Basic ROS knowledge | ||
- | * UE4 basic tutorials | ||
- | 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. |
- | == Kitchen Activity Games in a Realistic Robotic Simulator (BA/MA)== | + | Contact: [[team:gayane_kazhoyan|Gayane Kazhoyan]] |
- | | + | |
- | 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 | ||
- | Contact: [[team:andrei_haidu|Andrei Haidu]] | + | == Integrating PR2 in the Unreal Game Engine Framework (BA)== |
+ | | ||
- | == Integrating | + | Integrating the [[https://www.willowgarage.com/ |
- | | + | |
- | + | ||
- | Integrating the eye tracker in the [[http://gazebosim.org/|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: | Requirements: | ||
* Good programming skills in C/C++ | * Good programming skills in C/C++ | ||
- | * Gazebo simulator | + | * Basic physics/ |
+ | * Basic ROS knowledge | ||
+ | * UE4 basic tutorials | ||
Contact: [[team: | Contact: [[team: | ||
- | == Hand Skeleton Tracking Using Two Leap Motion Devices (BA/MA)== | ||
- | {{ : | ||
- | Improving the skeletal tracking offered by the [[https:// | + | == Realistic Grasping |
- | The tracked hand can then be used as input for the Kitchen Activity Games framework. | + | {{ : |
- | Requirements: | + | The objective of the project is to implement var- |
- | * Good programming skills | + | ious human-like grasping approaches |
- | Contact: [[team: | + | The game consist of a household environment where a user has to execute various given tasks, such as cooking a dish, setting the table, cleaning the dishes etc. The interaction is done using various sensors to map the users hands onto the virtual hands in the game. |
- | == Fluid Simulation in Gazebo | + | In order to improve the ease of manipulating objects the user should |
- | {{ :research: | + | be able to switch during runtime the type of grasp (pinch, power |
+ | grasp, precision grip etc.) he/she would like to use. | ||
+ | |||
+ | Requirements: | ||
+ | * Good programming skills in C++ | ||
+ | * Good knowledge of the Unreal Engine API. | ||
+ | * Experience with skeletal control / animations / 3D models in Unreal Engine. | ||
- | [[http:// | ||
- | Currently there is an [[http:// | + | Contact: [[team/andrei_haidu|Andrei Haidu]] |
- | The computational method for the fluid simulation is SPH (Smoothed-particle Dynamics), however newer and better methods based on SPH are currently present | + | == Kitchen Activity Games in a Realistic Robotic Simulator |
- | 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). | + | Developing new activities |
- | + | ||
- | Another topic would be the visualization of the fluid, currently is done by rendering every particle. For the rendering engine | + | |
- | + | ||
- | Here is a [[https:// | + | |
Requirements: | Requirements: | ||
* Good programming skills in C/C++ | * Good programming skills in C/C++ | ||
- | * Interest in Fluid simulation | ||
* Basic physics/ | * Basic physics/ | ||
- | * Gazebo simulator | + | * Gazebo simulator basic tutorials |
Contact: [[team: | Contact: [[team: | ||
- | |||
- | |||
- | == Automated sensor calibration toolkit (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, | ||
- | |||
- | The topic for this thesis is to develop an automated system for calibrating cameras, especially RGB-D cameras like the Kinect v2. | ||
- | |||
- | {{ : | ||
- | 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: | ||
- | * Good programming skills in Python and C/C++ | ||
- | * ROS, OpenCV | ||
- | |||
- | [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: | ||
- | |||
- |
Prof. Dr. hc. Michael Beetz PhD
Head of Institute
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ai-office@cs.uni-bremen.de
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