TU Berlin

Robotics and Biology LaboratoryManuel Baum

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Manuel Baum


Room: MAR 5.065
Telephone: +49.30.314-73119
Fax: +4930 314-21116
Office hours: On request    

Research interests

A large part of the robotics community develops specialized tools to solve specific problems. If we want to compose these tools into a larger system that behaves puroposefully, then we need to understand how these methods can interact with each other. I want to find out how we can organize such processes that generate behavior.

The domain in which I examine this is robotic manipulation. Right now, I am interested in the relation between motion planning and motion control. These are problems and methods on different scales of time and space, yet time and space are continuous, so a hard cut between such methods may be deficient.

I believe that a system which generates behavior should reflect the discreteness and continuousness of its problem setting. The analysis and decomposition of problem structure can naturally lead to a suitable decomposition of a system that acts to solve such a problem. I try to understand how such decomposition can be done automatically.

A first step towards this was my master's thesis where I worked with MMC, a kind of neural network that decomposes the computation of robot kinematics into the simultaneous solution of multiple smaller problems.

I am also interested in pattern formation, procedural geometry, drawing and painting.


Manuel Baum and Matthew Bernstein and Roberto Martín-Martín and Sebastian Höfer and Johannes Kulick and Marc Toussaint and Alex Kacelnik and Oliver Brock 2017. Opening a Lockbox through Physical Exploration. Proceedings of the IEEE International Conference on Humanoid Robots (Humanoids).

Manuel Baum and Oliver Brock 2017. Achieving Robustness by Optimizing Failure Behavior. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 5806-5811..

Manuel Baum and Martin Meier and Malte Schilling 2015. Population based Mean of Multiple Computations networks: A building block for kinematic models. 2015 International Joint Conference on Neural Networks (IJCNN), 1–8..



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