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teaching:gsoc2018 [2018/01/21 20:29] – balintbe | teaching:gsoc2018 [2018/01/23 08:35] – [Google Summer of Code 2018] ahaidu | ||
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====== Google Summer of Code 2018 ====== | ====== Google Summer of Code 2018 ====== | ||
~~NOTOC~~ | ~~NOTOC~~ | ||
+ | |||
+ | In the following we shortly present the [[# | ||
+ | |||
+ | For the **proposed topics** see [[# | ||
+ | |||
+ | |||
+ | ===== Software ===== | ||
+ | |||
===== pracmln ===== | ===== pracmln ===== | ||
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RoboSherlock builds on top of the ROS ecosystem and is able to wrap almost any existing perception algorithm/ | RoboSherlock builds on top of the ROS ecosystem and is able to wrap almost any existing perception algorithm/ | ||
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+ | ===== openEASE -- Web-based Robot Knowledge Service ===== | ||
+ | |||
+ | OpenEASE is a generic knowledge database for collecting and analyzing experiment data. Its foundation is the KnowRob knowledge processing system and ROS, enhanced by reasoning mechanisms and a web interface developed for inspecting comprehensive experiment logs. These logs can be recorded for example from complex CRAM plan executions, virtual reality experiments, | ||
+ | |||
+ | The OpenEASE web interface as well as further information and publication material can be accessed through its publicly available [[http:// | ||
+ | |||
+ | ===== RobCoG - Robot Commonsense Games ===== | ||
+ | |||
+ | [[http:// | ||
+ | |||
+ | The games are split into two categories: (1) VR/Full Body Tracking with physics based interactions, | ||
+ | |||
+ | |||
+ | ===== 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 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:// | ||
+ | [[http:// | ||
+ | and tutorials that help to get started. | ||
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- | ==== Topic 1: Multi-modal Cluttered Scene Analysis in Knowledge Intensive Scenarios | + | ==== Topic 2: Felxible perception pipeline manipulation for RoboSherlock |
{{ : | {{ : | ||
- | **Main Objective: | + | **Main Objective: |
- | able robots | + | |
- | cult and challenging scenarios. To achieve this the participant will | + | |
- | develop annotators | + | |
- | object-hypotheses generation | + | |
- | essentially means to generate regions/ | + | |
- | form a single object or object-part. In particular this entails | + | |
- | velopment | + | |
- | or object properties, as the likes of transparent objects, or cluttered, | + | |
- | occluded scenes. The addressed scenarios include stacked, occluded | + | |
- | objects placed on shelves, objects in drawers, refrigerators, | + | |
- | ers, cupboards etc. In typical scenarios, these confined spaces also | + | |
- | bare an underlying structure, which will be exploited, and used as | + | |
- | background knowledge, to aid perception (e.g. stacked plates would | + | |
- | show up as parallel lines using an edge detection). Specifically we | + | |
- | would start from (but not necessarly limit ourselves to) the implemen- | + | |
- | tation of two state-of-the-art algorithms described in recent papers: | + | |
- | [1] Aleksandrs Ecins, Cornelia Fermuller and Yiannis Aloimonos, Cluttered Scene Segmentation Using the Symmetry Constraint, International Conference on Robotics and Automation(ICRA) 2016 | + | **Task Difficulty: |
- | [2] Richtsfeld A., M ̈ | + | |
- | orwald T., Prankl J., Zillich M. and Vincze | + | |
- | M. - Segmentation of Unknown Objects in Indoor Environments. | + | |
- | IEEE/RSJ International Conference on Intelligent Robots and Sys- | + | |
- | tems (IROS), 2012. | + | |
- | + | ||
- | **Task Difficulty: | + | |
| | ||
**Requirements: | **Requirements: | ||
- | **Expected Results: | + | **Expected Results: |
Contact: [[team/ | Contact: [[team/ | ||
+ | ==== Topic 3: Unreal - ROS 2 Integration ==== | ||
+ | |||
+ | {{ : | ||
+ | |||
+ | TODO | ||
+ | |||
+ | **Task Difficulty: | ||
+ | | ||
+ | **Requirements: | ||
+ | |||
+ | **Expected Results** We expect to have an integrated communication level with ROS 2 and Unreal Engine on Windows and Linux side. | ||
+ | |||
+ | Contact: [[team/ | ||
+ | |||
+ | |||
+ | ==== Topic 4: Unreal Editor User Interface Development ==== | ||
+ | |||
+ | {{ : | ||
+ | |||
+ | TODO | ||
+ | |||
+ | **Task Difficulty: | ||
+ | | ||
+ | **Requirements: | ||
+ | |||
+ | **Expected Results** We expect to have intuitive Unreal Engine UI Panels for editing, visualizing various RobCoG plugins data and features. | ||
+ | |||
+ | Contact: [[team/ | ||
+ | |||
+ | |||
+ | ==== Topic 5: Unreal - openEASE Live Connection ==== | ||
+ | |||
+ | {{ : | ||
+ | |||
+ | TODO | ||
+ | |||
+ | **Task Difficulty: | ||
+ | | ||
+ | **Requirements: | ||
+ | |||
+ | **Expected Results** We expect to have a live connection with between openEASE and the Unreal Engine editor. | ||
+ | |||
+ | Contact: [[team/ | ||
+ | |||
+ | |||
+ | ==== Topic 6: CRAM -- Visualizing Robot' | ||
+ | |||
+ | {{ : | ||
+ | |||
+ | **Main Objective: | ||
+ | |||
+ | **Task Difficulty: | ||
+ | |||
+ | |||
+ | {{ : | ||
+ | |||
+ | **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). | ||
+ | |||
+ | **Expected Results:** We expect operational and robust contributions to the source code of the existing robot control system including documentation. | ||
+ | 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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