Reinhard Lafrenz

Evaluating Coupled Selection Equations for Dynamic Task Assignment Using a Behavior Framework

In this paper we focus on methods for a reliable and robust mechanism to distribute roles among a team of cooperating robots. In previous work, we showed the principal applicability of a novel approach based on self organization using coupled selection equations. To show the applicability in the robocup scenario we used a simple scenario to assign the roles attacker and defender. In this paper we present the application of the novel approach to more realistic and complex scenarios like kick-off or pass play. One of the critical parts in this method is the parameterization of utility and activation functions used to determine the additional parameters.

COMROS - A Multi-Agent Robot Architecture

In this paper we propose a refined version of the COMROS multi agent robot architecture. The concepts we use to define the operational principles of our architecture are autonomy of each functional module, task decomposition, and decentralized control. The structure of our architecture is defined by elementary agents which are connected by two types of networks. Furthermore, we describe how formation driving can be realized within the architecture.

Control of Autonomous Robots in the RoboCup Scenario Using Coupled Selection Equations

Concepts of self-organization, adapted from physics, chemistry or biology [1], [2], [3] are more and more important for the implementation of suitable control mechanisms in the field of artificial intelligent systems and especially in the field of distributed autonomous mobile robotic systems. These concepts seem to be very promising to guarantee the required flexibility, robustness and fault tolerance.

Physical Simulation of the Dynamical Behavior of Three-Wheeled Omni-directional Robots

Hardware simulation is a very efficient way for parameter tuning. We developed a Simulink-based simulator for the navigation components of our robotic soccer team. This physical simulation has interfaces to be interconnected with the higher levels of the real control software and is therefore able to perform an overall simulation of single robots.

A cooperative architecture to control multi-agent based robots

Internal Structure of a Robot. To control a group of cooperating autonomous mobile robots, we use a multi-agent architecture as introduced in [LBLM98]. The structure of a single robot consists of a set of concurrent Elementary Agents situated on different levels of abstraction. The levels are defined by different response time and are structured as reflexive, tactical, and strategical layer. E.g. in the reflexive layer tasks like object recognition and self-localization are processed.

Experimental study of self-organized fault-tolerant behavior in robotic systems

Concepts of self-organization, adapted from physics, chemistry or biology [4], [3], [7] will become more and more important for the implementation of suitable control mechanisms in the field of artificial intelligent systems and especially in the field of distributed autonomous mobile robotic systems. These concepts seem to be very promising to guarantee the required flexibility, robustness and fault-tolerance.

Kooperative Bildverarbeitung und Lokalisierung in einem Team von Robotern

In der vorliegenden Arbeit wird der Begriff der visuellen Kooperation bzw. kooperativen Bildverarbeitung definiert, analysiert und in Bezug gesetzt zum Schichtenmodell der Bildverarbeitung. Wie sich zeigen wird, kann durch die Verteilung der Sichtaufgabe auf mehrere raumlich getrennte Beobachter eines Teams die Zuverlassigkeitsrate bei der Erkennung gesteigert werden. Die Vorteile solch eines verteilten Sehens liegen in der Nutzung von potentiellem Wissen des Teams, in der Analyse von Szenen mit statischen oder dynamischen Objekten sowie in der Generierung robuster Hypothesen. Verteilt berechnete Daten lassen sich jedoch im allgemeinen nur dann kombinieren, wenn sie in Bezug zueinander gesetzt werden konnen. Diese Fahigkeit zur Selbstlokalisierung eines Beobachters, z.B. eines Roboters, bildet damit die Voraussetzung zur visuellen Kooperation. Nach einer kurzen Einfuhrung in die Problemstellung der Selbstlokalisierung schliest dieser Bericht mit Anwendungsbeispielen zu visueller Kooperation aus der high-level Bildverarbeitung vorgestellt.