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jobs [2015/10/15 09:22] – [Theses and Jobs] froggy86 | jobs [2017/05/03 12:37] – gkazhoya | ||
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+ | == Lisp / CRAM support assistant (HiWi) == | ||
- | == Kitchen Activity Games in a Realistic Robotic Simulator (BA/ | + | Technical support for the group for Lisp and the CRAM framework. |
- | {{ : | + | 8-16 hours per week for up to 1 year (paid). |
- | + | ||
- | Developing new activities | + | |
Requirements: | Requirements: | ||
- | * Good programming skills in C/C++ | + | * Good programming skills in Common Lisp |
- | * Basic physics/ | + | * Basic ROS knowledge |
- | * Gazebo simulator 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. |
- | == Integrating Eye Tracking in the Kitchen Activity Games (BA/MA)== | + | Contact: [[team:gayane_kazhoyan|Gayane Kazhoyan]] |
- | | + | |
- | Integrating the eye tracker in the [[http:// | ||
- | Requirements: | ||
- | * Good programming skills in C/C++ | ||
- | * Gazebo simulator basic tutorials | ||
- | Contact: [[team:andrei_haidu|Andrei Haidu]] | + | == Integrating PR2 in the Unreal Game Engine Framework (BA)== |
+ | | ||
- | == Hand Skeleton Tracking Using Two Leap Motion Devices (BA/MA)== | + | Integrating |
- | {{ : | + | |
- | + | ||
- | 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. | + | |
- | + | ||
- | The tracked hand can then be used as input for the Kitchen Activity Games framework. | + | |
- | + | ||
- | Requirements: | + | |
- | * Good programming skills in C/C++ | + | |
- | + | ||
- | Contact: [[team: | + | |
- | + | ||
- | == Fluid Simulation in Gazebo (BA/MA)== | + | |
- | {{ : | + | |
- | + | ||
- | [[http://gazebosim.org/ | + | |
- | + | ||
- | 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://www.ogre3d.org/ | + | |
- | + | ||
- | 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 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: | + | 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/ |
- | * ROS, OpenCV, PCL | + | * Gazebo simulator basic tutorials |
- | Contact: [[team:thiemo_wiedemeyer|Thiemo Wiedemeyer]] | + | Contact: [[team:andrei_haidu|Andrei Haidu]] |
- | + | ||
- | == 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: | + | |
- | + | ||
- | == Robot control systems in underwater robotics == | + | |
- | + | ||
- | The use of robots in underwater missions shows a challenging task. The dynamic terrain and its different conditions makes it difficult for robots to perform tasks correctly. In order to accomplish tasks in a proper way, the robot control routines have to be coordinated. The topic of this thesis is to develop robot control systems for underwater robotics in an underwater mission in order to navigate and to execute tasks correctly in the terrain. | + | |
- | + | ||
- | Requirements: | + | |
- | * Good programming skills in C/C++ or JAVA | + | |
- | * basic knowledge of ROS, OpenCV | + | |
- | + | ||
- | 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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