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.

Technical support for the group for Lisp and the CRAM framework.
5 hours per week for up to 1 year (paid).

Requirements:

• Good programming skills in Common Lisp
• Basic ROS knowledge

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.

Contact: Gayane Kazhoyan

Integrating the PR2 robot with ROS support in the Unreal Engine 4 Framework.

Requirements:

• Good programming skills in C/C++
• Basic physics/rendering engine knowledge
• Basic ROS knowledge
• UE4 basic tutorials

Contact: Andrei Haidu

The objective of the project is to implement var- ious human-like grasping approaches in a game developed using Unreal Engine.

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.

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:

• Good programming skills in C++
• Good knowledge of the Unreal Engine API.
• Experience with skeletal control / animations / 3D models in Unreal Engine.

Contact: Andrei Haidu

Developing new activities and improving the current simulation framework done under the Gazebo robotic simulator. Creating a custom GUI for the game, in order to launch new scenarios, save logs etc.

Requirements:

• Good programming skills in C/C++
• Basic physics/rendering engine knowledge
• Gazebo simulator basic tutorials

Contact: Andrei Haidu

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.

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://www.halcon.de/

Contact: Alexis Maldonado and Thiemo Wiedemeyer

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.

Requirements:

• Good programming skills in C/C++
• strong background in computer vision
• ROS, OpenCV, PCL

Contact: Thiemo Wiedemeyer

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:

• Good programming skills in C/C++
• strong background in computer vision
• Gazebo, OpenCV, PCL

Contact: Ferenc Balint-Benczedi

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: Ferenc Balint-Benczedi