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teaching:gsoc2014 [2014/02/25 13:26] – created tenorth | teaching:gsoc2014 [2014/02/25 13:31] – [Topic 2: CRAM -- Symbolic Reasoning Tools with Bullet] tenorth | ||
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====== Google Summer of Code 2014 ====== | ====== Google Summer of Code 2014 ====== | ||
+ | ~~NOTOC~~ | ||
Two software libraries that origin from our laboratory and that are now used | Two software libraries that origin from our laboratory and that are now used | ||
and supported by a larger user community are the KnowRob system for robot | and supported by a larger user community are the KnowRob system for robot | ||
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website]]. | website]]. | ||
+ | |||
+ | ===== Proposed Topics ===== | ||
+ | |||
+ | ==== CRAM -- Virtual Robot Scenarios in Gazebo ==== | ||
+ | **Main Objective: | ||
+ | for human-sized robots. This is done using ROS, the Gazebo robot | ||
+ | simulator, and CRAM. The scenarios to develop range from setups for | ||
+ | comparatively simple tasks, such as pick and place, to more sophisticated | ||
+ | workspaces requiring interaction with the environment, | ||
+ | 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. | ||
+ | The produced code will, when working in a simulated environment, | ||
+ | |||
+ | **Task Difficulty: | ||
+ | **Requirements: | ||
+ | **Expected Results:** We expect operational and robust | ||
+ | contributions to the software library that can be used as part of a | ||
+ | robot' | ||
+ | |||
+ | ==== Topic 2: CRAM -- Symbolic Reasoning Tools with Bullet ==== | ||
+ | |||
+ | **Main Objective: | ||
+ | **Task Difficulty: | ||
+ | **Requirements: | ||
+ | **Expected Results:** We expect operational and robust contributions to the software library that can be used as part of a robot' | ||
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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