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TU Berlin

Inhalt des Dokuments

Motion Planning Under Contact and Uncertainty with Dynamic Simulation

master thesis

Motivation Uncertainty is a major obstacle for robots manipulating objects in the real world. A robot can never perfectly know its position in the world, the position of objects, and the outcome of its actions. A particularly hard challenge is motion planning under uncertainty. How should the robot move, if the model of the world might be wrong or incomplete?  However, a robot can significantly reduce uncertainty if it uses contact sensing to establish controlled contact with the environment. Imagine a robot pushing objects into an edge of the environment - this action will reduce uncertainty over all objects positions. 

Description of Work

In our lab we implemented a sampling-based motion planner that combines controlled contact with configuration-space search (https://www.youtube.com/watch?v=mUbjuJ4pk8s). However, our planner is currently limited to static scenes and does not incorporate actions such as pushing or grasping. In this project you will use our uncertainty-based RRT-planner with a dynamic simulation including movable objects (using the bullet physics engine).

For this project you need good C++ programming skills. Experience with the roboticslibrary (from our robotics and compbio classes) or bullet physics is a plus.

People

Előd Páll
Manuel Baum
Oliver Brock

 

 

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