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teaching:gsoc2014 [2014/02/25 13:40] – [Google Summer of Code 2014] tenorthteaching:gsoc2014 [2014/02/25 14:14] – tenorth
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-{{ :teaching:gsoc-logo.png?nolink&200| }}+{{ :teaching:gsoc:gsoc-logo.png?nolink&200| }}
 ====== Google Summer of Code 2014 ====== ====== Google Summer of Code 2014 ======
 ~~NOTOC~~ ~~NOTOC~~
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 ==== CRAM -- Virtual Robot Scenarios in Gazebo ==== ==== CRAM -- Virtual Robot Scenarios in Gazebo ====
 +{{  :teaching:gsoc:open_drawer.png?nolink&150|}}
 **Main Objective:** The development of scenarios and tasks **Main Objective:** The development of scenarios and tasks
 for human-sized robots. This is done using ROS, the Gazebo robot for human-sized robots. This is done using ROS, the Gazebo robot
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 and closing drawers and doors. and closing drawers and doors.
 This involves designing virtual environments for Gazebo and/or writing robot plans in Lisp using the CRAM high-level language, sending commands to virtual PR2 or REEM(-C) robots in Gazebo, and manipulating the artificial environment in there. The connection to an elaborate high-level system holds a lot of interesting opportunities. This involves designing virtual environments for Gazebo and/or writing robot plans in Lisp using the CRAM high-level language, sending commands to virtual PR2 or REEM(-C) robots in Gazebo, and manipulating the artificial environment in there. The connection to an elaborate high-level system holds a lot of interesting opportunities.
 +{{  :teaching:gsoc:reem_standing.png?nolink&150|}}
 The produced code will, when working in a simulated environment, be run on the real robot in our laboratory and become part of the high-level behaviour library for the connected robots. The produced code will, when working in a simulated environment, be run on the real robot in our laboratory and become part of the high-level behaviour library for the connected robots.
  
 **Task Difficulty:** The difficulty depends on the environment setup and task chosen. The design of pick and place scenarios in a simple environment work towards ensuring the system's robustness, while more elaborate interaction tasks require more situational intelligence in the robot plan.\\ **Task Difficulty:** The difficulty depends on the environment setup and task chosen. The design of pick and place scenarios in a simple environment work towards ensuring the system's robustness, while more elaborate interaction tasks require more situational intelligence in the robot plan.\\
 **Requirements:** At least basic understanding in functional programming is advisable (ideally Lisp), basic knowledge in ROS helps, and ideally already having experience in simulation environments.\\ **Requirements:** At least basic understanding in functional programming is advisable (ideally Lisp), basic knowledge in ROS helps, and ideally already having experience in simulation environments.\\
 +{{  :teaching:gsoc:reem_c_sitting.png?nolink&150|}}
 **Expected Results:** We expect operational and robust **Expected Results:** We expect operational and robust
 contributions to the software library that can be used as part of a contributions to the software library that can be used as part of a
 robot's control program.} robot's control program.}
  
-==== Topic 2: CRAM -- Symbolic Reasoning Tools with Bullet ====+  
  
 +==== Topic 2: CRAM -- Symbolic Reasoning Tools with Bullet ====
 +{{  :teaching:gsoc:handle_detection_2.png?nolink&200|}}
 **Main Objective:**Mapping the environment to the internal belief state representation and keeping track of changes in the environment to keep the belief state up to date based on manipulation and interaction tasks performed by the robot.\\   **Main Objective:**Mapping the environment to the internal belief state representation and keeping track of changes in the environment to keep the belief state up to date based on manipulation and interaction tasks performed by the robot.\\  
 **Task Difficulty:** Relatively simple, when making the existing track changes more robust, and more challenging when introducing new change tracking (like noting the angle of open doors after opening them and storing it in the belief state).\\   **Task Difficulty:** Relatively simple, when making the existing track changes more robust, and more challenging when introducing new change tracking (like noting the angle of open doors after opening them and storing it in the belief state).\\  
 +{{  :teaching:gsoc:pr2_dishwasher.jpg?nolink&200|}}
 **Requirements:** At least basic understanding in functional programming is advisable (ideally Lisp), basic knowledge in ROS helps. Also a good understanding of geometric shapes and coordinate transformations helps.\\ **Requirements:** At least basic understanding in functional programming is advisable (ideally Lisp), basic knowledge in ROS helps. Also a good understanding of geometric shapes and coordinate transformations helps.\\
 **Expected Results:** We expect operational and robust contributions to the software library that can be used as part of a robot's control **Expected Results:** We expect operational and robust contributions to the software library that can be used as part of a robot's control
  
 ==== Topic 3: KnowRob -- Reasoning about 3D CAD models of objects ==== ==== Topic 3: KnowRob -- Reasoning about 3D CAD models of objects ====
 +<html><div style="float:right; margin-left:10px;"><iframe src="//player.vimeo.com/video/83977706" width="300" height="200" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe></div></html>
 **Main Objective:** Whenever robots interact with objects, they **Main Objective:** Whenever robots interact with objects, they
 need information about their geometry. While the overall shape is  need information about their geometry. While the overall shape is 
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