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jobs [2015/06/19 12:58] – winkler | jobs [2022/06/13 06:25] – [Research assistants (f/m/d)] dkastens | ||
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- | ~~NOTOC~~ | ||
- | =====Theses and Jobs===== | ||
- | If you are looking for a bachelor/ | ||
+ | =====Open researcher positions===== | ||
+ | - | ||
- | == HiWi-Position: | ||
- | When dealing with real-world robot tasks, simulation that is close to reality is key to test behavior-driven, | + | =====Theses and Student Jobs===== |
+ | If you are looking for a bachelor/ | ||
- | Requirements: | ||
- | * Experience in ROS | ||
- | * Passion for Robotics | ||
- | * Ideally programming skills in Lisp, Prolog, and Java | ||
- | Contact: [[team: | + | < |
+ | == Physics-based grasping in VR with finger tracking(Student Job / HiWi) == | ||
+ | Implementing physics-based grasping models in virtual environments, | ||
+ | using Manus VR. | ||
- | == GPU-based Parallelization of Numerical Optimization Techniques (BA/MA/HiWi)== | + | Requirements: |
+ | * Good C++ programming skills | ||
+ | * Familiar with skeletal animations | ||
+ | * Experience with simulators/ | ||
+ | * Familiar with Unreal Engine API | ||
+ | * Familiar with version-control systems (git) | ||
+ | * Able to work independently with minimal supervision | ||
- | 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. | + | Contact: [[team: |
+ | --></ | ||
- | Requirements: | ||
- | * Skills in numerical optimization algorithms | ||
- | * Good programming skills in Python and C/C++ | ||
- | Contact: [[team: | + | < |
+ | == Lisp / CRAM support assistant (HiWi) == | ||
- | == Online Learning of Markov Logic Networks | + | Technical support |
- | + | 8+ hours per week for up to 1 year (paid). | |
- | Markov Logic Networks (MLNs) combine | + | |
Requirements: | Requirements: | ||
- | * Experience | + | * Good programming skills |
- | * Experience with statistical relational learning (e.g. MLNs) is helpful. | + | * Basic ROS knowledge |
- | * Good programming skills in Python. | + | |
- | 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. |
+ | Contact: [[team: | ||
+ | --></ | ||
- | ==HiWi-Position: Knowledge Representation & Language Understanding for Intelligent Robots== | + | < |
+ | == Mesh Editing / Mesh Segmentation/ | ||
+ | {{ : | ||
- | In the context of the European research project RoboHow.Cog [1,2] we | + | Editing and cutting |
- | 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 | + | |
- | development and the integration of probabilistic methods | + | |
- | + | ||
- | 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 | + | * Good knowledge |
- | * Basic skills in Artificial Intelligence | + | * Familiar with Blender / Maya (or other) |
- | * Optional: basic skills in Probability Theory | + | |
- | * Optional: basic skills in Machine Learning | + | |
- | * Good programming skills in Python and Java | + | |
- | Hours: 10-20 h/week | + | Contact: [[team/ |
+ | --></html> | ||
- | Contact: [[team: | ||
- | [1] www.robohow.eu\\ | + | < |
- | [2] http://www.youtube.com/ | + | == 3D Animation and Modeling (Student Job / HiWi)== |
+ | {{ : | ||
+ | Developing and improving existing or new 3D (static/ | ||
+ | models in Blender / Maya (or other). Further importing and testing the | ||
+ | models against Unreal Engine. | ||
- | == Kitchen Activity Games in a Realistic Robotic Simulator (BA/ | + | Bonus: Working with state of the art 3D Scanners |
- | | + | |
- | + | ||
- | Developing new activities and improving the current simulation framework done under the [[http://gazebosim.org/|Gazebo]] robotic simulator. Creating a custom GUI for the game, in order to launch | + | |
Requirements: | Requirements: | ||
- | * Good programming skills in C/C++ | + | * Experience with Blender |
- | * Basic physics/rendering engine knowledge | + | * Knowledge of Unreal Engine material |
- | * Gazebo simulator basic tutorials | + | * Familiar with version-control systems (git) |
+ | * Able to work independently with minimal supervision | ||
Contact: [[team: | Contact: [[team: | ||
+ | --></ | ||
- | == Integrating Eye Tracking in the Kitchen Activity Games (BA/MA)== | + | == Linking saref to SOMA (BA Thesis) == |
- | {{ : | + | |
- | Integrating the eye tracker | + | Wissensrepräsentation: |
- | Requirements: | + | Aufgaben: |
- | * Good programming skills in C/C++ | + | * Arbeit mit Wissensrepräsentation und Wissensgraphen |
- | * Gazebo simulator basic tutorials | + | * Wissensakquisition aus web-Quellen |
+ | * Abfrage mit KnowRob (Prolog) für autonome Roboter | ||
- | Contact: [[team:andrei_haidu|Andrei Haidu]] | + | Contact: [[team:michaela_kümpel|Michaela Kümpel]] |
- | == Hand Skeleton Tracking Using Two Leap Motion Devices | + | == Case Study: Wissen zu Produkt-Aufbewahrungsorten aus dem Internet beziehen |
- | {{ : | + | |
- | Improving the skeletal tracking offered by the [[https:// | + | In dieser Thesis soll untersucht werden, ob die Autonomie von Robotern durch Integration von Wissen zu Aufbewahrungsorten von Produkten aus dem Internet erhöht werden kann. Es gibt verschiedene websites, die Wissen dazu bereitstellen. Dieses Wissen soll von den websites abgefragt und anschließend sinnvoll ontologisiert werden. Anhand verschiedener Fragen werden die Ergebnisse evaluiert (Menge der erworbenen Informationen/ Nutzen der Information, v.a. für autonome Roboter...) |
- | The tracked hand can then be used as input for the Kitchen Activity Games framework. | + | Aufgaben: |
+ | * Wissensakquise aus dem Internet | ||
+ | * Wissensrepräsentation/ | ||
+ | * Vergleich mit bestehenden Ontologien/ Arbeiten und manuell erstellten Ontologien | ||
+ | * Sinnvolle, automatisierte Abfrage des neu gewonnenen Wissens | ||
- | Requirements: | ||
- | * Good programming skills in C/C++ | ||
- | Contact: [[team:andrei_haidu|Andrei Haidu]] | + | Contact: [[team:michaela_kümpel|Michaela Kümpel]] |
- | == Fluid Simulation in Gazebo | + | == Integration of novel objects into Digital Twin Knowledge Bases (MA Thesis) == |
- | {{ : | + | |
- | [[http:// | + | In this thesis, the goal is to make a robotic system learn new objects automatically. |
+ | The system should be able to generate | ||
- | Currently there is an [[http://gazebosim.org/ | + | The focus of the thesis would be two-fold: |
+ | * Develop methods to automatically infer the object class of new objects. This would include perceiving it with state of the art sensors, constructing a 3d model of it and then infer the object class from online information sources. | ||
+ | * In the second step the system should also infer factual knowledge about the object from the internet and assert it into a robotic knowledgebase. Such knowledge could for example include the category of this product, typical object properties like its weight or typical location and much more. | ||
- | 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:// | ||
- | |||
- | Here is a [[https:// | ||
Requirements: | Requirements: | ||
- | * Good programming skills in C/C++ | + | * Knowledge about sensor data processing |
- | * Interest in Fluid simulation | + | * Interest in model construction from sensory data |
- | * Basic physics/ | + | * Work with KnowRob |
- | * Gazebo simulator and Fluidix basic tutorials | + | |
- | Contact: [[team: | ||
+ | Contact: [[team: | ||
- | == Automated sensor calibration toolkit | + | < |
+ | == Development of Modules for Robot Perception | ||
+ | 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: | ||
+ | * Software development to create Interfaces between ROS and Unreal Engine 4 (mainly C++) | ||
+ | * Software development for our Robot Perception framework [[http:// | ||
- | Computer vision is an important part of autonomous robots. For robots the image sensors are the main source of information | + | Requirements: |
+ | * Experience in C++. | ||
+ | * Basic understanding | ||
+ | The spoken language | ||
- | The topic for this thesis is to develop an automated system for calibrating cameras, especially RGB-D cameras like the Kinect v2. | + | Contact: [[team: |
+ | --></ | ||
- | {{ : | + | == Game Engine Developer |
- | The system should: | + | A recent development in the field of AI is the usage of photorealistic simulations, |
- | * be independent of the camera type | + | In our research group, we focus on the development of modern robots that can make use of the potential of game engines. This requires a high degree of specialized game engine plugins that can simulate certain aspects of our research. Another important task is the creation of 3d models. |
- | * estimate intrinsic | + | |
- | * calibrate depth images | + | |
- | | + | |
- | * operate autonomously | + | |
- | Requirements: | + | Therefore, we are currently offering multiple Hiwi positions / student jobs for the following tasks: |
- | * Good programming skills | + | * Modelling of objects for the use in Unreal Engine 4. |
- | * ROS, OpenCV | + | * Creation of specific simulation aspects in Unreal Engine 4. For example the development of interactable objects. |
- | [1] http:// | + | Requirements: |
- | + | * Knowledge | |
- | Contact: [[team: | + | * Experience |
- | + | ||
- | == 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 | + | |
- | + | ||
- | 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 | + | |
- | * 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: | + | The spoken language |
- | * Good programming skills | + | |
- | * 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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