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teaching:gsoc2017 [2017/02/08 08:10] – [Proposed Topics] liscateaching:gsoc2017 [2017/02/08 08:11] – [Topic 1: Multi-modal Cluttered Scene Analysis in Knowledge Intensive Scenarios] lisca
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 Contact: [[team/ferenc_balint-benczedi|Ferenc Bálint-Benczédi]] Contact: [[team/ferenc_balint-benczedi|Ferenc Bálint-Benczédi]]
 +
 +==== Topic 2: Realistic Grasping using Unreal Engine ====
 +
 +{{  :teaching:gsoc:topic2_unreal.png?nolink&200|}}
 +
 +**Main Objective:** The objective of the project is to implement var-
 +ious human-like grasping approaches in a game developed using [[https://www.unrealengine.com/|Unreal Engine]]. 
 +
 +The game consist of a household environment where a user has to execute various given tasks, such as cooking a dish, setting the table, cleaning the dishes etc. The interaction is done using various sensors to map the users hands onto the virtual hands in the game.
 +
 +In order to improve the ease of manipulating objects the user should
 +be able to switch during runtime the type of grasp (pinch, power
 +grasp, precision grip etc.) he/she would like to use.
 +
 +**Task Difficulty:** The task is to be placed in the easy difficulty
 +level, as it requires less algorithmic knowledge and more programming skills.
 +  
 +**Requirements:** Good programming skills in C++. Good knowledge of the Unreal Engine API. Experience with skeletal control / animations / 3D models in Unreal Engine.
 +
 +**Expected Results** We expect to enhance our currently developed robot learning game with realistic human-like grasping capabilities. These would allow users to interact more realistically with the given virtual environment. Having the possibility to manipulate objects of various shapes and sizes will allow to increase the repertoire of the executed tasks in the game. Being able to switch between specific grasps will allow us to learn grasping models specific to each manipulated object.
 +
 +Contact: [[team/andrei_haidu|Andrei Haidu]]
  
  




Prof. Dr. hc. Michael Beetz PhD
Head of Institute

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