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| teaching:gsoc2018 [2018/01/22 13:03] – gkazhoya | teaching:gsoc2018 [2018/01/23 08:44] – [Topic 3: Unreal - ROS 2 Integration] ahaidu |
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| ====== Google Summer of Code 2018 ====== | ====== Google Summer of Code 2018 ====== |
| ~~NOTOC~~ | ~~NOTOC~~ |
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| | In the following we shortly present the [[#software|open source frameworks]] that are participating for this year's Google Summer of Code. |
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| | For the **proposed topics** see [[#proposed_topics|section]] further below. |
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| | ===== Software ===== |
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| ===== pracmln ===== | ===== pracmln ===== |
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| CRAM is an open-source project hosted on [[https://github.com/cram2/cram|GitHub.]] It has its own | CRAM is an open-source project hosted on [[https://github.com/cram2/cram|GitHub.]] It has its own |
| project page ([[http://cram-system.org]]) that provides extensive documentation | [[http://cram-system.org|project page]] that provides extensive documentation |
| and tutorials that help to get started. | and tutorials that help to get started. |
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| ==== Topic 2: Felxible perception pipeline manipulation for RoboSherlock ==== | ==== Topic 2: Felxible perception pipeline manipulation for RoboSherlock ==== |
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| {{ :teaching:gsoc:topic1_rs.png?nolink&200|}} | {{ :teaching:gsoc:topic1_rs.png?nolink&140|}} |
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| **Main Objective:** RoboSherlock is based on the unstructured information management paradigm and uses the uima library at it's core. The c++ implementation of this library is limited multiple ways. In this topic you will develop a module in order to flexibly manage perception pipelines by extending the current implementation to enable new modalities and run pipelines in parallel. This involves implementing an API for pipeline and data handling that is rooted in the domain of UIMA. | **Main Objective:** RoboSherlock is based on the unstructured information management paradigm and uses the uima library at it's core. The c++ implementation of this library is limited multiple ways. In this topic you will develop a module in order to flexibly manage perception pipelines by extending the current implementation to enable new modalities and run pipelines in parallel. This involves implementing an API for pipeline and data handling that is rooted in the domain of UIMA. |
| ==== Topic 3: Unreal - ROS 2 Integration ==== | ==== Topic 3: Unreal - ROS 2 Integration ==== |
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| {{ :teaching:gsoc:ue_ros2.png?nolink&200|}} | {{ :teaching:gsoc:ue_ros2.png?nolink&150|}} |
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| TODO | Since [[https://github.com/ros2/ros2/wiki|ROS2]] has cross platform support, it would be of a great advantage to wrap it as a module in the Unreal Engine framework. This would greatly improve communication between our RobCoG modules and the ROS world. As a further step the module should be extended to work under Linux as well. This can be done using the unreal build system ([[https://docs.unrealengine.com/latest/INT/Programming/UnrealBuildSystem/|UBT]]). |
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| **Task Difficulty:** The task is to be placed in the medium difficulty level, as it requires programming skills of various frameworks (ROS, Linux, Unreal Engine). | **Task Difficulty:** The task is to be placed in the medium difficulty level, as it requires programming skills of various frameworks (ROS, Linux, Unreal Engine). |
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| Contact: [[team/andrei_haidu|Andrei Haidu]], [[team/asil_kaan_bozcuoglu|Asil Kaan Bozcuoğlu]] | Contact: [[team/andrei_haidu|Andrei Haidu]], [[team/asil_kaan_bozcuoglu|Asil Kaan Bozcuoğlu]] |
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| | ==== Topic 6: CRAM -- Visualizing Robot's Simulation World in RViz ==== |
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| | {{ :teaching:fetch-left-in-hand-cropped.png?nolink&200|}} |
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| | **Main Objective:** CRAM includes a fast simulation engine for developers to test their newly written plans and for robots to try out different parameters of an action before executing it in the real world. Currently, the world is only visualized using raw OpenGL rendering. The objective of this topic is to visualize the robot's simulation world in the ROS visualization tool RViz, including the state of the robot itself, the objects surrounding it and the reasoning processes involved in action execution. |
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| | **Task Difficulty:** The task itself is simple assuming good understanding of ROS principles and basic knowledge of RViz. To that the challenge of learning a small chuck of an existing system (CRAM) is added. So overall task difficulty is considered to be medium. |
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| | {{ :teaching:fetch-left-in-hand-real-cropped.jpg?nolink&200|}} |
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| | **Requirements:** |
| | * Familiarity with functional programming paradigms: some functional programming experience is a requirement (preferred language is Lisp but Haskel, Scheme, OCaml, Clojure, Scala or similar will do); |
| | * Experience with ROS (Robot Operating System). |
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| | **Expected Results:** We expect operational and robust contributions to the source code of the existing robot control system including documentation. |
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| | Contact: [[team/gayane_kazhoyan|Gayane Kazhoyan]] |
