Publications

Titles

Evolutionary Gait-Optimization Using a Fitness Function Based on Proprioception

Röfer, T. (2004)
In: RoboCup 2004, Lecture Notes in Artificial Intelligence, Springer.
[Abstract]

An Egocentric Qualitative Spatial Knowledge Representation Based on Ordering Information

Wagner, T. and Huebner, K. (2004)
In: RoboCup 2004, Lecture Notes in Artificial Intelligence, Springer.
[Abstract]

A Behavior Architecture for Autonomous Mobile Robots Based on Potential Fields

Laue, T. and Röfer, T. (2004)
In: RoboCup 2004, Lecture Notes in Artificial Intelligence, Springer.
[Abstract]

RoboCup 2004 Competitions and Symposium: A Small Kick for Robots, a Giant Score for Science

Lima, P., Custódio, L., Akin, L., Jacoff, A., Kraezschmar, G., Kiat, N. B., Obst, O., Röfer, T., Takahashi, Y., Zhou, C. (2005)
In: AI Magazine. American Association for Artificial Intelligence.

A Symmetry Operator and its Application to the RoboCup

Huebner, K. (2003)
In: RoboCup 2003, Lecture Notes in Artificial Intelligence, Springer.
[Abstract]

Recognition and prediction of motion situations based on a qualitative motion description

Miene, A. and Visser, U. and Herzog, O. (2003)
In: RoboCup 2003, Lecture Notes in Artificial Intelligence, Springer.
[Abstract]

Fast and Robust Edge-Based Localization in the Sony Four-Legged Robot League

Röfer, T. and Jüngel, M. (2003)
In: RoboCup 2002, Lecture Notes in Artificial Intelligence, Springer.
[Abstract]

Vision-Based Fast and Reactive Monte-Carlo Localization

Röfer, T., Jüngel, M. (2003)
In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA-2003), Taipei, Taiwan. 856-861.
[Abstract] [.pdf]

Using Online Learning to Analyze the Opponent's Behavior

Visser, Ubbo and Weland, Hans-Georg
In: RoboCup 2002, Lecture Notes in Artificial Intelligence, Springer. 78-93.
[Abstract] [.pdf]

Decision-making and Tactical Behavior with Potential Fields

Meyer, Jens and Adolph, Robert and Stephan, Daniel and Daniel, Andreas and Seekamp, Matthias and Weinert, Volker and Visser, Ubbo
In: RoboCup 2002, Lecture Notes in Artificial Intelligence, Springer. 304-311.
[Abstract] [.pdf]

An Architecture for a National RoboCup Team

T. Röfer (2003)
In: RoboCup 2002, Lecture Notes in Artificial Intelligence, Springer. 417-425.
[Abstract] [.pdf]

GermanTeam 2001

R. Brunn and U. Düffert and M. Jüngel and T. Laue and M. Lötzsch and S. Petters and M. Risler and T. Röfer and K. Spiess and A. Sztybryc (2002)
In: RoboCup 2001, Lecture Notes in Artificial Intelligence, Springer.
[Abstract] [.pdf]

GermanTeam 2001

H.-D. Burkhard and U. Düffert and M. Jüngel and M. Lötzsch and N. Koschmieder and T. Laue and T. Röfer and K. Spiess and A. Sztybryc and R. Brunn and M. Risler and O. v. Stryk
[Abstract] [.pdf]

"As time goes by" - Using time series based decision tree induction to analyze the behaviour of opponent players

Drücker, Christian and Hübner, Sebastian and Visser, Ubbo and Weland, Hans-Georg (2001)
In: RoboCup 2001: 325-330
[Abstract] [.pdf]

Interpretation of spatio-temporal relations in real-time and dynamic environments

Miene, Andrea and Visser, Ubbo (2001)
In: RoboCup 2001: 441-447
[Abstract] [.pdf]

Recognizing Formations in Opponent Teams

Visser, Ubbo and Drücker, Christian and Hübner, Sebastian and Schmidt, Esko and Weland, Hans-Georg (2000)
In: RoboCup 2000, Lecture Notes in Artificial Intelligence, Springer. 391-396
[Abstract] [.pdf]

Abstracts

Evolutionary Gait-Optimization Using a Fitness Function Based on Proprioception

Röfer, T.

An Egocentric Qualitative Spatial Knowledge Representation Based on Ordering Information

Wagner, T. and Huebner, K.

Navigation is one of the most fundamental tasks to be accomplished by many types of mobile and cognitive systems. Most approaches in this area are based on building or using existing allocentric, static maps in order to guide the navigation process. In this paper we propose a simple egocentric, qualitative approach to navigation based on ordering information. An advantage of our approach is that it produces qualitative spatial information which is required to describe and recognize complex and abstract, i.e., translation-invariant behavior. In contrast to other techniques for mobile robot tasks, that also rely on landmarks it is also proposed to reason about their validity despite insufficient and insecure sensory data. Here we present a formal approach that avoids this problem by use of a simple internal spatial representation based on landmarks aligned in an extended panoramic representation structure.

A Behavior Architecture for Autonomous Mobile Robots Based on Potential Fields

Laue, T. and Röfer, T.

A Symmetry Operator and its Application to the RoboCup

Huebner, K.

At present, visual localization of soccer playing robots taking part in the RoboCup contest is mainly achieved by using colored artificial landmarks. As known, this method causes further vision problems like color classification and segmentation under variable light conditions. Additionally, robots confined to use visual sensor information from common cameras usually waste time in switching between the modi of playing soccer and searching landmarks for localization. An upcoming approach to solve these problems is the detection of field lines. Motivated by our research in using a compact symmetry operator for natural feature extraction in mobile robot applications, we propose its application to the RoboCup contest. Symmetry is a structural feature and as results show, it is highly independent of illumination changes and very compliant to the task of line detection. We will motivate symmetry as a natural feature, discuss the symmetry operator and finally present results of the field line extraction.

Recognition and prediction of motion situations based on a qualitative motion description

Miene, A. and Visser, U. and Herzog, O.

High-level online methods become more and more attractive with the increasing abilities of players and teams in the simulation league. As in real soccer, the recognition and prediction of strategies (e.g. opponent’s formation), tactics (e.g. wing play, offside traps), and situations (e.g. passing behavior) is important. In 2001, we proposed an approach where spatio-temporal relations between objects are described and interpreted in order to detect some of the above mentioned situations. In this paper we propose an extension of this approach that enables us to both interpret and predict complex situations. It is based on a qualitative description of motion scenes and additional background knowledge. The method is applicable to a variety of situations. Our experiment consists of numerous offside situations in simulation league games.We discuss the results in detail and conclude that this approach is valuable for future use because it is (a) possible to use the method in real-time, (b) we can predict situations giving us the option to refine agents actions in a game, and (c) it is domain independent in general.

Fast and Robust Edge-Based Localization in the Sony Four-Legged Robot League

Röfer, T. and Jüngel, M.

This paper presents a fast approach for edge-based selflocalization in RoboCup. The vision system extracts edges between the field and field lines, borders, and goals following a grid-based approach without processing whole images. These edges are employed for the selflocalization of the robot. Both image processing and self-localization work in real-time on a Sony Aibo, i. e. at the frame rate of the camera. The localization method was evaluated using a laser range sensor at the field border as a reference system.

Vision-Based Fast and Reactive Monte-Carlo Localization

Röfer, T., Jüngel, M.

This paper presents a fast approach for vision-based self-localization in RoboCup. The vision system extracts the features required for localization without processing the whole image and is a first step towards independence of lighting conditions. In the field of self-localization, some new ideas are added to the well-known Monte-Carlo localization approach that increase both stability and reactivity, while keeping the processing time low.

[.pdf]

An Architecture for a National RoboCup Team

T. Röfer

This paper describes the architecture used by the GermanTeam 2002 in the Sony Legged Robot League. It focuses on the special needs of a national team, i.e. a “team of teams” from different universities in one country that compete against each other in national contests, but that will jointly line up at the international RoboCup championship. In addition, the tools developed by the GermanTeam will be presented, e.g. the first 3-D simulation used in the Sony Legged Robot League.

[.pdf]

GermanTeam 2001

R. Brunn and U. Düffert and M. Jüngel and T. Laue and M. Lötzsch and S. Petters and M. Risler and T. Röfer and K. Spiess and A. Sztybryc

Short team description of the GermanTeam 2001 in the Sony Legged Robot League.

[.pdf]

GermanTeam 2001

H.-D. Burkhard and U. Düffert and M. Jüngel and M. Lötzsch and N. Koschmieder and T. Laue and T. Röfer and K. Spiess and A. Sztybryc and R. Brunn and M. Risler and O. v. Stryk

The GermanTeam is a joint project of several Germa n universities in the Sony Legged Robot League. This report describes the software developed for the RoboCup 2001 in Seattle. It presents the software architecture of the system as well as the methods that were developed to tackle the problems of motion, image processing, object recognition, self-localization, and robot behavior. The approaches for both playing robot soccer and mastering the challenges are presented. In addition to the software actually running on the robots, this document will also give an overview of the tools the GermanTeam used to support the development process.

[.pdf]

"As time goes by" - Using time series based decision tree induction to analyze the behaviour of opponent players

Drücker, Christian and Hübner, Sebastian and Visser, Ubbo and Weland, Hans-Georg

With the more sophisticated abilities of teams within the simulation league high level online functions become more and more attractive. Last year we proposed an approach to recognize the opponents strategy and developed the online coach accordingly. However, this approach gives only information about the entire team and is not able to detect significant situations (e.g. double pass, standard situations). In this paper we describe a new method which describes spatio-temporal relations between objects. This approach is able to track the objects and therefore the relations between them online so that we are able to interpret situations over time during the game. This enables us to detect the above mentioned situations. We can implement this in the online coach in order to enrich our team with high level functions. This new method is domain independent.

[.pdf]

Interpretation of spatio-temporal relations in real-time and dynamic environments

Miene, Andrea and Visser, Ubbo

[.pdf]

Recognizing Formations in Opponent Teams

Visser, Ubbo and Drücker, Christian and Hübner, Sebastian and Schmidt, Esko and Weland, Hans-Georg

The online coach within the simulation league has become more powerful over the last few years. Therefore, new options with regard to the recognition of the opponents strategy are possible. For example, the online coach is the only player who gets the information of all the objects on the field. This leads to the idea determine the opponents play system by the online coach and then choose an effective counter-strategy. This has been done with the help of an artificial neural network and will be discussed in this paper. All soccer-clients are initialized with a specific behavior and can change their behavior to an appropriate mode depending on the coach's commands. The result is a flexible and effective game played by the eleven soccer-clients.

[.pdf]

Decision-making and Tactical Behavior with Potential Fields

Meyer, Jens and Adolph, Robert and Stephan, Daniel and Daniel, Andreas and Seekamp, Matthias and Weinert, Volker and Visser, Ubbo

Using potential-fields is a seldomly used technique in RoboCup scenarios. The existing approaches mainly concentrate on world state representation on single actions such as a kick. In this paper we will show how to apply potential fields to assist fast and precise decisions in an easy and intuitive way. We go beyond the existing approaches in using potential fields to determine all possible player actions, basic and advanced tactics an also general player behaviors. To ensure fast computing we mainly use basic mathematical computation for potential field related calculations. This gives us the advantage of both determining and understanding player actions. Therefore, integrating future features such as a complex online coach and progressive localization methods will be easier. We implemented the approach in our team Bremen University Goal Seekers (BUGS) and tested it in numerous games against other simulation league teams. The results show that CPU-time of making a decision per team has been decreased significantly. This is a crucial improvement for calculations in time-critical environments.

[.pdf]

Using online learning to analyze the opponents behavior

Visser, Ubbo and Weland, Hans-Georg

Analyzing opponent teams has been established within the simulation league for a number of years. However, most of the analyzing methods are only available off-line. Last year we introduced a new idea which uses a time series-based decision tree induction to generate rules on-line. This paper follows that idea and introduces the approach in detail. We implemented this approach as a library function and are therefore able to use on-line coaches of various teams in order to test the method. The tests are based on two 'models' (a) the behavior of a goalkeeper, and (b) the pass behavior of the opponent players. The approach generates propositional rules (first rules after 1000 cycles) which have to be pruned and interpreted in order to use this new knowledge for one's own team. We discuss the outcome of the tests in detail and conclude that on-line learning despite of the lack of time is not only possible but can become an effective method for one's own team.

[.pdf]

Author: Kai Hübner

SPP RoboCup

Last updated: September 18, 2004