I have finished my work in the Intelligent Autonomous Systems Group and don't continue working in this area. For questions about my work, please contact Prof. Michael Beetz. The title of my PhD Thesis is:

Transformational Planning for Autonomous Household Robots using Libraries of Robust and Flexible Plans

In my work I developed TRANER (Transformational Planner for Everyday Activity). In a simulated kitchen environment I investigated how a robot can accomplish everyday tasks und how it can adapt to the environment and improve its behavior. The basic idea of TRANER is demonstrated in this video.

• PhD Thesis (5.3 MB, PDF)
• Slides (1.8 MB, PDF)
• Slides and videos (106 MB, ZIP, Some videos are encoded with XVID)

Former Research Projects

• Cogito : 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.

• 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.

Teaching

Student Projects

• DA: Concurrent Execution of Robot Plans for Every-day Activities using Learned Prediciton Models (Marc Bachmann)
• SEP: Implementational Aspects of Application-specific Plans for Autonomous Household Robots (Marc Bachmann)
• DA: Designing Libraries of Transparent, General and Restartable Activity Plans for a Simulated Autonomous Service Robot (Andreas Häusler) [pdf]
• SEP: Simulation realistischer Perzeptionsmodelle für autonome Roboter (Sonja Wöhnl)
• DA: KitchenBotSim - A Simulator for Autonomous Mobile Household Robots with a Realistic Physical Model (Daniel Poza Zamarrón)
• SEP: Lernen von leistungsstarken Navigationsroutinen für autonome Fußballroboter (Michael Schweitzer) [ps]

Courses as a PhD Student/Researcher

• Preparing and supervising the lab course AI-based Robot Control (WS 2007/08)
• Preparing exercises for lecture Introduction to Computer Science 3 (hardware-near programming) (WS 2005/06)
• Preparing and supervising the lab course Applications of Knowledge-based Systems: Intelligent Systems (SS 2005, WS 2004/05, SS 2004, WS 2003/04)

Courses as a Student

• Assistance in preparing and supervising the lab course Applications of Knowledge-based Systems: Intelligent Systems (WS 2002/03)
• Tutor for lecture Introduction to Computer Science 4 (theoretical computer science) (SS 2002)
• Tutor for lecture Introduction to Computer Science 3 (hardware-near programming) (WS 2001/02)
• Assistance in preparing and supervising the lab course Functional Programming and Compiler Construction (WS 2001/2002)

Selected Publications

• Armin Müller , Transformational Planning for Autonomous Household Robots using Libraries of Robust and Flexible Plans, 2008,

  (BibTeX) (PDF)

• Michael Beetz , Jan Bandouch , Alexandra Kirsch , Alexis Maldonado , Armin Müller , Radu Bogdan Rusu , The Assistive Kitchen --- A Demonstration Scenario for Cognitive Technical Systems, 2007, Proceedings of the 4th COE Workshop on Human Adaptive Mechatronics (HAM),

  (BibTeX) (PDF)

• Armin Müller , Alexandra Kirsch , Michael Beetz , Transformational Planning for Everyday Activity, 2007, Proceedings of the 17th International Conference on Automated Planning and Scheduling (ICAPS'07),

  (BibTeX) (PDF)

• Armin Müller , Michael Beetz , Towards a Plan Library for Household Robots, 2007, Proceedings of the ICAPS'07 Workshop on Planning and Plan Execution for Real-World Systems: Principles and Practices for Planning in Execution,

  (BibTeX) (PDF)

• Armin Müller , Michael Beetz , Designing and Implementing a Plan Library for a Simulated Household Robot, 2006, Cognitive Robotics: Papers from the AAAI Workshop,

  (BibTeX) (PDF)