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~~NOTOC~~ | ~~NOTOC~~ | ||
- | =====Theses and Jobs===== | ||
- | If you are looking for a bachelor/ | ||
+ | =====Open researcher positions===== | ||
+ | ====Digital Twin Knowledge Base for submarine robot inspection/ | ||
+ | The Institute for Artificial Intelligence (IAI) investigates methods for cognition-enabled robot control. The research is at the intersection of robotics and Artificial Intelligence and includes methods for intelligent perception, dexterous object manipulation, | ||
- | == GPU-based Parallelization | + | As a researcher |
- | 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. | + | **Prerequisites: |
+ | * Digital Twins | ||
+ | * Knowledge Representation | ||
+ | * Data structures | ||
+ | * Data Stream Representation. | ||
- | Requirements: | + | **Hiring institution:** University of Bremen |
- | | + | |
- | | + | |
- | Contact: [[team: | + | **PhD Enrollment:** PhD position in the Institute for Artificial Intelligence at University of Bremen. The project involves collaboration with ROSEN in Bremen and UiO in Oslo. |
- | == Online Learning | + | The PhD examination acceptance requires a “Certificate |
- | 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, | + | **Duration |
- | Requirements: | + | **Main Academic Supervisor:** Prof. Michael Beetz, contact: beetz@cs.uni-bremen.de |
- | | + | |
- | | + | |
- | * Good programming skills in Python. | + | |
- | Contact: [[team: | + | **Co-supervisors:** prof. Einar Broch Johnsen (UiO, Norway), dr. Peter Kampmann (ROSEN, Germany) |
+ | =====Theses and Student Jobs===== | ||
+ | If you are looking for a bachelor/ | ||
- | ==HiWi-Position: Knowledge Representation & Language Understanding for Intelligent Robots== | + | == Physics-based grasping in VR with finger tracking(Student Job / HiWi) == |
- | In the context of the European research project RoboHow.Cog [1,2] we | + | Implementing physics-based grasping models |
- | are investigating methods for combining multimodal sources of knowledge (e.g. video, natural-language recipes or computer games), | + | using Manus VR. |
- | + | ||
- | 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' | + | |
- | + | ||
- | Tasks: | + | |
- | * 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' | + | * Good C++ programming skills |
- | * Basic skills in Artificial Intelligence | + | * Familiar with skeletal animations |
- | * Optional: basic skills in Probability Theory | + | * Experience with simulators/ |
- | * Optional: basic skills in Machine Learning | + | * Familiar with Unreal Engine API |
- | * Good programming skills in Python and Java | + | * Familiar with version-control systems (git) |
+ | * Able to work independently with minimal supervision | ||
- | Hours: 10-20 h/week | + | Contact: [[team: |
- | Contact: [[team: | ||
- | [1] www.robohow.eu\\ | ||
- | [2] http:// | ||
+ | < | ||
+ | == 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+ 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://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. | + | < |
+ | == Mesh Editing | ||
+ | {{ : | ||
- | Requirements: | + | Editing and cutting a human mesh into different parts in Blender |
- | * Good programming skills | + | |
- | * Gazebo simulator basic tutorials | + | |
- | + | ||
- | Contact: [[team: | + | |
- | + | ||
- | == Hand Skeleton Tracking Using Two Leap Motion Devices | + | |
- | {{ : | + | |
- | + | ||
- | Improving the skeletal tracking offered by the [[https:// | + | |
- | + | ||
- | The tracked hand can then be used as input for the Kitchen Activity Games framework. | + | |
Requirements: | Requirements: | ||
- | * Good programming skills | + | * Good knowledge |
- | + | * Familiar with Blender | |
- | Contact: [[team: | + | |
- | + | ||
- | == Fluid Simulation in Gazebo | + | |
- | {{ : | + | |
- | [[http:// | + | Contact: |
+ | --></ | ||
- | 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 | + | == 3D Animation |
+ | {{ : | ||
- | Another topic would be the visualization of the fluid, currently is done by rendering every particle. For the rendering engine [[http://www.ogre3d.org/ | + | Developing and improving existing or new 3D (static/skeletal) |
+ | models in Blender | ||
+ | models against Unreal Engine. | ||
- | Here is a [[https://vimeo.com/104629835|video]] example of the current state of the fluid in Gazebo. | + | Bonus: Working with state of the art 3D Scanners |
Requirements: | Requirements: | ||
- | * Good programming skills in C/C++ | + | * Experience with Blender |
- | * Interest in Fluid simulation | + | * Knowledge of Unreal Engine material / lightning development |
- | * Basic physics/ | + | * Familiar with version-control systems (git) |
- | * Gazebo simulator and Fluidix basic tutorials | + | * Able to work independently with minimal supervision |
Contact: [[team: | Contact: [[team: | ||
- | == Automated sensor calibration toolkit | + | == App zur Generierung von Ernährungsempfehlungen |
- | 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, | + | Dies ist ein Wissensrepräsentations-Thema. Basierend auf einem bestehenden Wissensgraphen mit Produktinformationen sollen weitere ernährungsspezifische Informationen wie z.B. Substitute für Rezeptzutaten oder Rezepte für spezielle Ernährungsgewohnheiten generiert werden. Diese Informationen müssen aus bestehenden web-Quellen extrahiert und mit dem Wissensgraphen verknüpft werden. Die Informationen sollen dann in einer Smartphone-App (Android) visualisiert werden. Dabei kann auf bestehenden Apps aufgebaut werden. |
- | The topic for this master thesis is to develop an automated system for calibrating cameras, especially RGB-D cameras like the Kinect v2. | + | Aufgaben: |
+ | * Arbeit mit Wissensrepräsentation und Wissensgraphen | ||
+ | * Wissensakquisition aus web-Quellen | ||
+ | * App Entwicklung mit der Unity game engine und/oder Flutter | ||
- | The system should be: | + | Contact: [[team: |
- | * independent of the camera type | + | |
- | * estimate intrinsics and extrinsics | + | |
- | * have depth calibration (case of RGBD) | + | |
- | * integrate capabilities from Halcon | + | |
- | Requirements: | + | == Sprachauswahl für Shopping Assistenten (BA Thesis) == |
- | * Good programming skills in Python and C/C++ | + | |
- | * ROS, OpenCV | + | |
- | [1] http://www.halcon.de/ | + | Weiterentwicklung eines Produktinformationssystems im Einzelhandel für Smartphones (Android) um eine Sprachauswahl. Anzeige der jeweiligen Informationen in der gewünschten Sprache. |
+ | Dabei wird auf bestehenden Apps aufgebaut. | ||
- | Contact: [[team: | + | Aufgaben: |
+ | * App Entwicklung mit der Unity game engine und Flutter | ||
+ | * Erweiterung der App um eine Sprachauswahl | ||
+ | * Arbeit mit Wissensrepräsentation und Wissensgraphen für Sprachmodellierung | ||
- | == 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, | + | Contact: [[team: |
- | Requirements: | + | == Situational awareness |
- | * Good programming skills | + | |
- | * strong background in computer vision | + | |
- | * ROS, OpenCV, PCL | + | |
- | Contact: [[team: | + | This is a knowledge representation topic including knowledge graphs. The idea is so link external Web-knowledge to an existing knowledge framework in order to include situational awareness so that a robot acting in a household environment can infer what an object is used for in a given situation. |
- | == Simulation of a robots belief state to support perception(MA) == | + | A result would be that a spoon next to a bowl with cereal would be used for eating while a spoon on a stove next to a pot would be used for stirring. |
- | Create | + | requirements: |
+ | * Work with KnowRob knowledge processing framework | ||
+ | * Work with knowledge graphs and Linked Data to create | ||
+ | * Implement reasoning about situations (based on perceived environment) | ||
- | Requirements: | ||
- | * Good programming skills in C/C++ | ||
- | * strong background in computer vision | ||
- | * Gazebo, OpenCV, PCL | ||
- | Contact: [[team:ferenc_balint-benczedi|Ferenc Balint-Benczedi]] | + | Contact: [[team:michaela_kümpel|Michaela Kümpel]] |
- | == Multi-expert segmentation of cluttered and occluded scenes == | ||
- | Objects | + | == Development of Modules for Robot Perception and Game Engine Technology (Hiwi Job) == |
+ | A recent development | ||
+ | In our research group, we focus on the development of modern robots that can make use of the potential of game engines. One particular research direction, is the combination of computer vision with game engines. | ||
+ | In this context, we are currently offering multiple Hiwi positions / student jobs for the following tasks: | ||
+ | * Modelling | ||
+ | * Creation of specific simulation aspects in Unreal Engine 4. For example the development of interactable objects. | ||
+ | * Software development | ||
+ | * Software development for our Robot Perception framework [[http:// | ||
- | 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:patrick_mania|Patrick Mania]] |
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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