Department of Computer Science Technische Universitaet Muenchen
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Ongoing research projects

AGILO - Semi-Automatic Acquisition of Visuomotoric Plans
http://ias.cs.tum.edu/projects/agilo/
Robotic soccer has become a standard 'real-world' testbed for autonomous multi robot control. In robot soccer (mid-size league) two teams of four autonomous robots --- one goal keeper and three field players --- play soccer against each other. The soccer field is four by nine meters big. The key characteristics of mid-size robot soccer are that the robots are completely autonomous. Consequently, all sensing and all action selection is done onboard of the individual robots. Skillful play requires our robots to recognize objects, such as other robots, field lines, and goals, and even entire game situations.

In the AGILO project we investigate how probabilistic visuomotoric autonomous robot controllers that are capable of learning can meet these challenges.

The AGILO robot controllers employ game state estimation and situated action selection based on automatically learned control mechanisms.

We are currently rebuilding the AGILO team using Roboteq controllers.

COGITO - Plan-based Control of Robotic Agents
A key challenge for the next generation of autonomous robots is the reliable and efficient accomplishment of prolonged, complex, and dynamically changing tasks in the real world.

One of the most promising approaches to realizing these capabilities is the plan-based approach to robot control. In the plan-based approach, robots produce control actions by generating, maintaining, and executing plans that are tailored for the robots' respective tasks. Plans are robot control programs that a robot can not only execute but also reason about and manipulate. Thus a plan-based controller is able to manage and adapt the robot's intended course of action --- the plan --- while executing it and can thereby better achieve complex and changing goals. The use of plans enables these robots to flexibly interleave complex and interacting tasks, exploit opportunities, quickly plan their courses of action, and, if necessary, revise their intended activities.

One of the grand visions in the area of plan-based robot control is the realization of general autonomous robot control programs that can adapt themselves to the environments they are to operate in and to the distribution of complex tasks they are to perform. An instance of this grand vision is a pre-programmed household robot that knows how to clean a kitchen, how to operate a dishwasher, and so on. Being installed in a new environment it specializes its general plans to the specifics of the household and learns to manage the specific agenda of household chorus that is given to it. The robot also has to learn about the pitfalls of its tasks and its environment and avoid them through foresight. Our research field is still far away from realizing such competent robotic agents.

I am currently working on machine learning/data mining techniques which will be later integrated in the COGITO project.

Past/finished researched projects
Please visit my personal web page for information about my "other" projects.

Computer Science IX | Technische Universität München