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jobs [2014/08/29 11:12] – [Theses and Jobs] ahaidujobs [2016/03/03 07:58] – [Theses and Jobs] ahaidu
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 If you are looking for a bachelor/master thesis or a job as a student research assistant, you may find some interesting opportunities on this page. If you are looking for a bachelor/master thesis or a job as a student research assistant, you may find some interesting opportunities on this page.
  
 +== Lisp / CRAM support assistant (HiWi) ==
  
- +Technical support for the group for Lisp and the CRAM framework. \\ 
-== GPU-based Parallelization of Numerical Optimization Techniques (BA/MA/HiWi)== +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 (e.g. CUDA) are to be investigated in order implement numerical optimizers that substantially profit from parallel execution.+
  
 Requirements: Requirements:
-  * Skills in numerical optimization algorithms +  * Good programming skills in Common Lisp 
-  * Good programming skills in Python and C/C++ +  * Basic ROS knowledge
- +
-Contact: [[team:daniel_nyga|Daniel Nyga]] +
- +
-== Online Learning of Markov Logic Networks for Natural-Language Understanding (MA)== +
- +
-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, which allow incremental learning, when new examples come in one-by-one. +
- +
-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]] +
  
-==HiWi-Position: Knowledge Representation & Language Understanding for Intelligent Robots==+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.
  
-In the context of the European research project RoboHow.Cog [1,2] we +Contact: [[team:gayane_kazhoyan|Gayane Kazhoyan]]
-are investigating methods for combining multimodal sources of knowledge (e.g. video, natural-language recipes or computer games), in order to enable mobile robots to autonomously acquire new high level skills like cooking meals or straightening up rooms.  +
  
-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's, Master's or Diploma Theses.+== Integrating PR2 in the Unreal Game Engine Framework (BA)== 
 + {{ :research:unreal_ros_pr2.png?200|}} 
  
-Tasks: +Integrating the [[https://www.willowgarage.com/pages/pr2/overview|PR2]] robot with [[http://www.ros.org/|ROS]] support in the [[https://www.unrealengine.com|Unreal Engine 4]] Framework.
-  * 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 in Computer Science (Bachelor's, Master's or Diploma) +  * Good programming skills in C/C++ 
-  * Basic skills in Artificial Intelligence +  * Basic physics/rendering engine knowledge 
-  * Optional: basic skills in Probability Theory +  * Basic ROS knowledge 
-  * Optional: basic skills in Machine Learning +  * UE4 basic tutorials
-  * Good programming skills in Python and Java+
  
-Hours: 10-20 h/week+Contact: [[team:andrei_haidu|Andrei Haidu]]
  
-Contact: [[team:daniel_nyga|Daniel Nyga]] 
  
-[1] www.robohow.eu\\ +== Realistic Grasping using Unreal Engine (BA/MA) ==
-[2] http://www.youtube.com/watch?v=0eIryyzlRwA+
  
 +{{  :teaching:gsoc:topic2_unreal.png?nolink&150|}}
  
-== Depth-Adaptive Superpixels (BA/MA)== +The objective of the project is to implement var- 
- {{ :research:dt_dasp.png?200|}} +ious human-like grasping approaches in a game developed using [[https://www.unrealengine.com/|Unreal Engine]]. 
-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 of DASP is not very performant for high resolution images, there are several options for doing a project in this field like reimplementing DASP using CUDA, investigating how thermal data can be integrated, ...+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.
  
-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:jan-hendrik_worch|Jan-Hendrik Worch]] 
- 
- 
-== Physical Simulation of Humans (BA/MA)== 
- {{ :research:human_model.png?200|}} 
- 
-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:jan-hendrik_worch|Jan-Hendrik Worch]]+Contact: [[team/andrei_haidu|Andrei Haidu]]
  
-== Kitchen Activity Games in a Realistic Robotic Simulator (BA/MA/HiWi)==+== Kitchen Activity Games in a Realistic Robotic Simulator (BA/MA)==
  {{ :research:gz_env1.png?200|}}   {{ :research:gz_env1.png?200|}} 
  
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 Contact: [[team:andrei_haidu|Andrei Haidu]] Contact: [[team:andrei_haidu|Andrei Haidu]]
  
-== Integrating Eye Tracking in the Kitchen Activity Games (BA/MA)== 
- {{ :research:eye_tracker.png?200|}}  
  
-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: 
-  * Good programming skills in C/C++ 
-  * Gazebo simulator basic tutorials 
  
-Contact: [[team:andrei_haidu|Andrei Haidu]]+== Automated sensor calibration toolkit (BA/MA)==
  
-== Hand Skeleton Tracking Using Two Leap Motion Devices (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, it is important that the parameters for the cameras in use are well known. The calibration of a camera is a time consuming task, and the result depends highly on the chosen setup and the accuracy of the operator.
- {{ :research:leap_motion.jpg?200|}} +
  
-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 topic for this thesis is to develop an automated system for calibrating cameras, especially RGB-D cameras like the Kinect v2.
  
-The tracked hand can then be used as input for the Kitchen Activity Games framework.+ {{ :kinect2_calibration_setup_small.jpg?200|}} 
 +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: +Requirements:  
-  * Good programming skills in C/C+++  * Good programming skills in Python and C/C++ 
 +  * ROS, OpenCV
  
-Contact: [[team:andrei_haidu|Andrei Haidu]]+[1] http://www.halcon.de/
  
-== Fluid Simulation in Gazebo (BA/MA)== +Contact: [[team:alexis_maldonado|Alexis Maldonado]] and [[team:thiemo_wiedemeyer|Thiemo Wiedemeyer]]
- {{ :research:fluid.png?200|}} +
  
-[[http://gazebosim.org/|Gazebo]] currently only supports rigid body physics engines (ODE, Bullet etc.), however in some cases fluids are preferred in order to simulate as realistically as possible the given environment.+== On-the-fly 3D CAD model creation (MA)==
  
-Currently there is an [[http://gazebosim.org/tutorials?tut=fluids&cat=physics|experimental version]] of fluids  in Gazebo, using the [[http://onezero.ca/fluidix/|Fluidix]] library to run the fluids computation on the GPU.+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, completing it's 3D model from multiple views improving redetection. Using the robots manipulator pick up the object and complete the model by viewing it from multiple viewpoints.
  
-The computational method for the fluid simulation is SPH (Smoothed-particle Dynamics), however newer and better methods based on SPH are currently present +Requirements:  
-and should be implemented (PCISPH/IISPH).+  * Good programming skills in C/C++ 
 +  * strong background in computer vision  
 +  * ROS, OpenCV, PCL
  
-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).+Contact: [[team:thiemo_wiedemeyer|Thiemo Wiedemeyer]]
  
-Another topic would be the visualization of the fluid, currently is done by rendering every particle. For the rendering engine [[http://www.ogre3d.org/|OGRE]] is used.+== Simulation of a robots belief state to support perception(MA) ==
  
-Here is a [[https://vimeo.com/104629835|video]] example of the current state of the fluid in Gazebo. +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, detection and tracking of these in the real world. 
  
-Requirements:+Requirements: 
   * Good programming skills in C/C++   * Good programming skills in C/C++
-  * Interest in Fluid simulation +  * strong background in computer vision  
-  * Basic physics/rendering engine knowledge +  * Gazebo, OpenCV, PCL 
-  * Gazebo simulator and Fluidix basic tutorials+ 
 +Contact: [[team:ferenc_balint-benczedi|Ferenc Balint-Benczedi]] 
 + 
 +== 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, combining the results of multiple segmentation algorithms in order to come up with more reliable object hypotheses. 
 + 
 +Requirements:  
 +  * Good programming skills in C/C++ 
 +  * strong background in 3D vision  
 +  * basic knowledge of ROS, OpenCV, PCL 
 + 
 +Contact: [[team:ferenc_balint-benczedi|Ferenc Balint-Benczedi]]
  
-Contact: [[team:andrei_haidu|Andrei Haidu]] 
  
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