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teaching:gsoc2018 [2018/01/22 13:01] – gkazhoya | teaching:gsoc2018 [2018/02/16 11:19] – [Topic 2: Felxible perception pipeline manipulation for RoboSherlock] 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 [[# | ||
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+ | For the **proposed topics** see [[# | ||
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+ | ===== Software ===== | ||
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===== pracmln ===== | ===== pracmln ===== | ||
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- | ===== CRAM - executive and toolbox for creating cognitive robot behavior | + | ===== CRAM - Cognition-enabled Robot Executive |
- | CRAM is a software toolbox for the design, implementation and deployment of cognition-enabled plan execution on autonomous robots. CRAM equips autonomous robots with lightweight reasoning mechanisms that can infer control decisions rather than requiring the decisions to be preprogrammed. This way CRAM-programmed autonomous robots are more flexible and general than control programs that lack such cognitive capabilities. CRAM does not require the whole reasoning domain to be stated explicitly in an abstract knowledge base. Rather, it grounds symbolic expressions into the perception and actuation routines and into the essential data structures of the control plans. | + | CRAM is a software toolbox for the design, implementation and deployment of cognition-enabled plan execution on autonomous robots. CRAM equips autonomous robots with lightweight reasoning mechanisms that can infer control decisions rather than requiring the decisions to be preprogrammed. This way CRAM-programmed autonomous robots are more flexible and general than control programs that lack such cognitive capabilities. CRAM does not require the whole reasoning domain to be stated explicitly in an abstract knowledge base. Rather, it grounds symbolic expressions into the perception and actuation routines and into the essential data structures of the control plans. CRAM includes a domain-specific language that makes writing reactive concurrent robot behavior easier for the programmer. It extensively uses the ROS middleware infrastructure. |
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- | CRAM includes a domain-specific language that makes writing reactive concurrent robot behavior easier for the programmer. It extensively uses the ROS middleware infrastructure. | + | |
CRAM is an open-source project hosted on [[https:// | CRAM is an open-source project hosted on [[https:// | ||
- | project page ([[http:// | + | [[http:// |
and tutorials that help to get started. | and tutorials that help to get started. | ||
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- | ==== Topic 2: Felxible | + | ==== Topic 2: Flexible |
- | {{ : | + | {{ : |
**Main Objective: | **Main Objective: | ||
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==== Topic 3: Unreal - ROS 2 Integration ==== | ==== Topic 3: Unreal - ROS 2 Integration ==== | ||
- | {{ : | + | {{ : |
- | TODO | + | Since [[https:// |
**Task Difficulty: | **Task Difficulty: | ||
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{{ : | {{ : | ||
- | TODO | + | For this topic we would like to extend the modules from RobCoG with intuitive Unreal Engine Editor Panels. This would allow easier and faster manipulation/ |
**Task Difficulty: | **Task Difficulty: | ||
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==== Topic 5: Unreal - openEASE Live Connection ==== | ==== Topic 5: Unreal - openEASE Live Connection ==== | ||
- | {{ : | + | {{ : |
- | TODO | + | For this topic we would like to create a live connection between openEASE and RobCoG. A user should be able to connect to openEASE from the Unreal Engine Editor and perform various queries. For example to verify if the items from the Unreal Engine world are present in the ontology of the robot. It should be able to upload new data directly from the editor. |
**Task Difficulty: | **Task Difficulty: | ||
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Contact: [[team/ | Contact: [[team/ | ||
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+ | ==== Topic 6: CRAM -- Visualizing Robot' | ||
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+ | {{ : | ||
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+ | **Main Objective: | ||
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+ | **Task Difficulty: | ||
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+ | {{ : | ||
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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/ | ||
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+ | ==== Topic 7: Robot simulation in Unreal Engine with PhysX ==== | ||
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+ | {{ : | ||
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+ | **Main Objective: | ||
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+ | **Task Difficulty: | ||
+ | level, as it requires programming skills of various frameworks (Unreal Engine, | ||
+ | PhysX), expertise in robotic simulation and physics engines. | ||
+ | | ||
+ | **Requirements: | ||
+ | of the Unreal Engine and PhysX API. Experience in robotics and robotic simulation is a plus. | ||
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+ | **Expected Results** We expect to be able to simulate robots in unreal, have support and able to control standard joints. | ||
+ | |||
+ | Contact: [[team/ |
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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