Hans Utz

Miro - middleware for mobile robot applications

Developing software for mobile robot applications is a tedious and error-prone task. Modern mobile robot systems are distributed systems, and their designs exhibit large heterogeneity in terms of hardware, operating systems, communications protocols, and programming languages. Vendor-provided programming environments have not kept pace with recent developments in software technology. Also, standardized modules for certain robot functionalities are beginning to emerge. Furthermore, the seamless integration of mobile robot applications into enterprise information processing systems is mostly an open problem. We suggest the construction and use of object-oriented robot middleware to make the development of mobile robot applications easier and faster, and to foster portability and maintainability of robot software. With Miro, we present such a middleware, which meets the aforementioned requirements and has been ported to three different mobile platforms with little effort. Miro also provides generic abstract services like localization or behavior engines, which can be applied on different robot platforms with virtually no modifications.

Miro: Middleware for Autonomous Mobile Robots

Abstract Implementing software for autonomous mobile robots is a non-trivial task, because such robots incorporate several sensor systems and actuators that must be controlled simultaneously by a heterogeneous ensemble of networked computers and microcontrollers. Additionally, the use of modern software engineering technologies like object-oriented and distributed programming and client/server architectures is essential in order to maintain program code effectively. In this paper, we present Miro, a new CORBA-based robot programming framework which allows a rapid development of reliable and safe software on heterogeneous computer networks and supports the mixed use of several programming languages.

Towards autonomous vision self-calibration for soccer robots

The ability to autonomously adapt to variations in the environmental conditions is a very useful feature for mobile robots. Of particular interest in robotic soccer are self-calibrating vision systems that automatically adapt to local lighting conditions. The paper presents a method for autonomous calibration of a color classificator used for color blob-based image segmentation and landmark and object recognition. The experimental results demonstrate significantly improved robustness of visual processing.

Playing Robot Soccer under Natural Light: A Case Study

The recent debate in the RoboCup middle-size community about natural light conditions shows that a more in-depth analysis of the problems incurred by this is necessary in order to draft out a focused and realistic roadmap for research. Based on real-world images taken under varying lighting conditions, we performed descriptive and statistical analysis of the effects on color-based vision routines. The results show that pure color-based image processing is not likely to perform well under varying lighting conditions, even if the vision system is calibrated on a per-game base. We conclude that color-based vision has to be combined with other methods and algorithms in order to work robustly in more difficult environments with varying illumination.

Miro - Middleware for Cooperative Robotics

Developing software for mobile robot applications is a tedious and error-prone task. We suggest the use of object-oriented middleware to remedy the problem. After identifying crucial design goals, we present Miro, an object-oriented middleware for robots meeting the design goals. We discuss its implementation and demonstrate Miros role in the implementation of applications on different kinds of robots.

Sharing belief in teams of heterogeneous robots

This paper describes the joint approach of three research groups to enable a heterogeneous team of robots to exchange belief. The communication framework presented imposes little restrictions on the design and implementation of the individual autonomous mobile systems. The three groups have individually taken part in the RoboCup F2000 league since 1998. Although recent rule changes allow for more robots per team, the cost of acquiring and maintaining autonomous mobile robots keeps teams from making use of this opportunity. A solution is to build mixed teams with robots from different labs. As almost all robots in this league are custom built research platforms with unique sensors, actuators, and software architectures, forming a heterogeneous team presents an exciting challenge.

Improving Vision-Based Self-localization

After removing the walls around the field, vision-based localization has become an even more interesting approach for robotic soccer. The paper discusses how removal of the wall affects the localization task in RoboCup, both for vision-based and non-visual approaches, and argues that vision-based Monte Carlo localization based on landmark features seems to cope well with the changed field setup. An innovative approach for landmark feature detection for vision-based Monte Carlo Localization is presented. Experimental results indicate that the approach is robust and reliable.

Hierarchical behavior organization

In most behavior-based approaches, implementing a broad set of different behavioral skills and coordinating them to achieve coherent complex behavior is an error-prone and very tedious task. Concepts for organizing reactive behavior in a hierarchical manner are rarely found in behavior-based approaches, and there is no widely accepted approach for creating such behavior hierarchies. Most applications of behavior-based concepts use only few behaviors and do not seem to scale well. Reuse of behaviors for different application scenarios or even on different robots is very rare, and the integration of behavior-based approaches with planning is unsolved. This paper discusses the design, implementation, and performance of a behavior framework that addresses some of these issues within the context of behavior-based and hybrid robot control architectures. The approach presents a step towards more systematic software engineering of behavior-based robot systems.

Coordination Without Negotiation in Teams of Heterogeneous Robots

A key feature of human cooperation is that we can coordinate well without communication or negotiation. We achieve this by anticipating the intentions and actions of others, and adapting our own actions to them accordingly. In contrast, most multi-robot systems rely on extensive communication to exchange their intentions. This paper describes the joint approach of our two research groups to enable a heterogeneous team of robots to coordinate implicitly, without negotiation. We apply implicit coordination to a typical coordination task from robotic soccer: regaining ball possession. We discuss the benefits and drawbacks of implicit coordination, and evaluate it by conducting several experiments with our robotic soccer teams.

The Ulm Sparrows 2001

The Ulm Sparrows team is a student-oriented, interdisciplinary research effort at the University of Ulm. The team is active in both the simulation and the middle-size league, but simulation efforts are targeted towards supporting the middle-size league robot team. We competed in the RoboCup World Championships in Paris (1998) [5] and Stockholm (1999, quarterfinals) [7], the European RoboCup Championships in Amsterdam (2000, semifinals) [4], plus a number of national events in Germany. For time and budget constraints, we could not participate in Melbourne in 2000.