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In this chapter we target the problem of monitoring an environment with a team of mobile robots having on board video-cameras and fixed stereo cameras available within the environment. Current research regards homogeneous robots, whereas in this chapter we study highly heterogeneous systems and consider the problem of patrolling an area with a dynamic set of agents. The system presented in the chapter provides enhanced multi-robot coordination and vision-based activity monitoring techniques. The main objective is the integration and development of coordination techniques for multi-robot environment coverage, with the goal of maximizing the quality of information gathered from a given area thus, implementing a Heterogeneous mobile and reconfigurable multi-camera video-surveillance system. [ABSTRACT FROM AUTHOR]

Studies of spatial representation generally focus on flat environments and visual stimuli. However, the world is not flat, and slopes are part of many natural environments. In a series of four experiments, we examined whether humans can use a slope as a source of allocentric, directional information for reorientation. A target was hidden in a corner of a square, featureless enclosure tilted at a 5° angle. Finding it required using the vestibular, kinesthetic and visual cues associated with the slope gradient. Participants succeeded in the task; however, a large sex difference emerged. Men showed a greater ability in using slope and a greater preference for relying on slope as a searching strategy. The female disadvantage was not due to wearing heeled shoes, but was probably related to a greater difficulty in extracting the vertical axis of the slope. [ABSTRACT FROM AUTHOR]

This paper presents a design of cooperative behaviors through Petri Net Plans, based on the principles provided by Cohen and Levesque΄s Joint Commitments Theory. Petri Net Plans are a formal tool that has proved very effective for the representation of multi-robot plans, providing all the means necessary for the design of cooperation. The Joint Commitment theory is used as a guideline to present a general multi-robot Petri Net Plan for teamwork, that can be used to model a wide range of cooperative behaviors. As an example we describe the implementation of a robotic-soccer passing task, performed by Sony AIBO robots. [ABSTRACT FROM AUTHOR]

In order to summarize the status of rescue robotics, this chapter will cover the basic characteristics of disasters and their impact on robotic design, describe the robots actually used in disasters to date, promising robot designs (e.g., snakes, legged locomotion) and concepts (e.g., robot teams or swarms, sensor networks), methods of evaluation in benchmarks for rescue robotics, and conclude with a discussion of the fundamental problems and open issues facing rescue robotics, and their evolution from an interesting idea to widespread adoption. The Chapter will concentrate on the rescue phase, not recovery, with the understanding that capabilities for rescue can be applied to, and extended for, the recovery phase. The use of robots in the prevention and preparedness phases of disaster management are outside the scope of this chapter. [ABSTRACT FROM AUTHOR]

The increasing interest towards rescue robotics and the complexity of typical rescue environments make it necessary to use high fidelity 3D simulators during the application development phase. USARSim is an open source high fidelity simulator for rescue environments, based on a commercial game engine. In this paper, we describe the development of an autonomous rescue robot within the USARSim simulation environment. We describe our rescue robotic system and present the extensions we made to USARSim in order to have a satisfying simulation of our robot. Moreover, as a case study, we present an algorithm to avoid obstacles invisible to our laser scanner based mapping process. [ABSTRACT FROM AUTHOR]

"RoboCup is an international joint project to promote AI, robotics, and related field. It is an attempt to foster AI and intelligent robotics research by providing a standard problem where wide range of technologies can be integrated and examined. RoboCup chose to use soccer game as a central topic of research, aiming at innovations to be applied for socially significant problems and industries."From the RoboCup Web site www.robocup.org The aim of the paper is to provide an AI research perspective on RoboCup, based on the experience gained partecipating in the competition, within our research group at "La Sapienza". [ABSTRACT FROM AUTHOR]

ITAS is a tool that allows a human to play soccer in the RoboCup Soccer Simulator environment. This is essentially the reverse challenge to that of RoboCup. Instead of bringing the machine to the real world, ITAS strives to seamlessly interface man to the machine world. This presents a fundamental human-computer interaction design problem. This paper shows how the reverse RoboCup challenge can benefit the RoboCup community and what value it brings to robotics and AI research in large. An overview of the features of ITAS and its development using the Usability Engineering Lifecycle are then given, followed by a comparison with a related system, OZ-RP. ITAS is an open source project. The most recent releases are available at http://itas.sourceforge.net. [ABSTRACT FROM AUTHOR]

The UT Austin Villa 2003 simulated online soccer coach was a first time entry in the RoboCup Coach Competition. In developing the coach, the main research focus was placed on treating advice-giving as a machine learning problem. Competing against a field of mostly hand-coded coaches, the UT Austin Villa coach earned first place in the competition. In this paper, we present the multi-faceted learning strategy that our coach used and examine which aspects contributed most to the coach's success. [ABSTRACT FROM AUTHOR]

UCHILSIM is a robotic simulator specially developed for the RoboCup four-legged league. It reproduces with high accuracy the dynamics of AIBO motions and its interactions with the objects in the game field. Their graphic representations within the game field also possess a high level of detail. The main design goal of the simulator is to become a platform for learning complex robotic behaviors which can be directly transferred to a real robot environment. UCHILSIM is able to adapt its parameters automatically, by comparing robot controller behaviors in reality and in simulations. So far, the effectiveness of UCHILSIM has been tested in some robot learning experiments which we briefly discuss hereinafter. We believe that the use of a highly realistic simulator might speed up the progress in the four legged league by allowing more people to participate in our challenge. [ABSTRACT FROM AUTHOR]

Component-based software engineering is useful for embedded applications such as robotics. However, heavyweight component systems such as CORBA overstrain the ressources available in many embedded systems. Here, a lightweight component-based approach is used to implement the system software of the so-called CubeSystem, CubeOS. Since 1998, CubeOS and its component system have been successfully used in various areas from industry projects over RoboCup-related research to edutainment applications. Many of the components used in RoboCup soccer have been carried over in the implementation of the IUB Rescue robots, demonstrating the potential for software reuse. [ABSTRACT FROM AUTHOR]

In the effort to meet the steadily changing demands of teaching computer science and computer engineering, new methods of learning and teaching are used by which multifarious knowledge and learning techniques can be imparted, practical skills and abilities can be developed and teamwork and creativity are encouraged. A promising attempt is the use of robotic construction kits. This paper portrays the educational environment that was used at the courses "Hamburg RoboCup: Mobile autonomous robots play soccer" at the University of Hamburg, Germany and "Advanced robotics - Soccer playing mobile autonomous robots" at the California State University of Chico, USA and compares the experiences made during both courses due to intercultural differences. [ABSTRACT FROM AUTHOR]

This article describes a software development toolkit for programming mobile robots, that has been used on different platforms and for different robotic application. In this paper we address design choices, implementation issues and results in the realization of our robot programming environment, that has been devised and built from many people since 1998. We believe that the proposed framework is extremely useful not only for experienced robotic software developers, but also for students approaching robotic research projects. [ABSTRACT FROM AUTHOR]

This paper describes methods used in stabilizing the walking gait of Tao-Pie-Pie, a small humanoid robot given rate feedback from two RC gyroscopes. Tao-Pie-Pie is a fully autonomous small humanoid robot (30cm tall). Although Tao-Pie-Pie uses a minimal set of actuators and sensors, it has proven itself in international competitions, winning honors at the RoboCup and HuroSot competitions in 2002 and 2003. The feedback control law is based solely on the rate information from two RC gyroscopes. This alleviates drift problems introduced by integrating the RC gyroscope feedback in the more common position control approaches. [ABSTRACT FROM AUTHOR]

Motion detection and tracking while moving is a desired ability for any soccer player. For instance, this ability allows the determination of the ball trajectory when the player is moving himself or when he is moving his head, for making or planning a soccer-play. If a robot soccer player should have a similar functionality, then it requires an algorithm for real-time movement analysis and tracking that performs well when the camera is moving. The aim of this paper is to propose such an algorithm for an AIBO robot. The proposed algorithm uses motion compensation for having a stabilized background, where the movement is detected, and Kalman Filtering for a robust tracking of the moving objects. The algorithm can be adapted for almost any kind of mobile robot. Results of the motion detection and tracking algorithm, working in real-world video sequences, are shown. [ABSTRACT FROM AUTHOR]

The paper discusses a top-down approach to model soccer knowledge, as it can be found in soccer theory books. The goal is to model soccer strategies and tactics in a way that they are usable for multiple RoboCup soccer leagues, i.e. for different hardware platforms. We investigate if and how soccer theory can be formalized such that specification and execution is possible. The advantage is clear: theory abstracts from hardware and from specific situations in leagues. We introduce basic primitives compliant with the terminology known in soccer theory, discuss an example on an abstract level and formalize it. We then consider aspects of different RoboCup leagues in a case study and examine how examples can be instantiated in three different leagues. [ABSTRACT FROM AUTHOR]

Soccer simulation commentary system is a suitable test bed for exploring real time systems. The rapidly changing simulation environment requires that the system generates real time comments based on the information received from the Soccer Server. In this article, a three-layer architecture of Caspian Soccer Commentary system is presented, and each component of the system is briefly described. The emphasis of this paper is on design and implementation of the Analyzer and the Content Selector subsystems. The Analyzer takes advantage of the State Machine to keep track of the game situations. The Scheduling and Interruption mechanism is proposed to improve the efficiency of the Content Selector subsystem. The presented Commentary System together with the other Caspian presentation and analysis tools won the first place in RoboCup 2003 Game Presentation and Match Analysis competitions. [ABSTRACT FROM AUTHOR]

In this study, a new method called Reverse Monte Carlo Localization (R-MCL) for global localization of autonomous mobile agents in the robotic soccer domain is proposed to overcome the uncertainty in the sensors, environment and the motion model. This is a hybrid method based on both Markov Localization(ML) and Monte Carlo Localization(MCL) where the ML module finds the region where the robot should be and MCL predicts the geometrical location with high precision by selecting samples in this region. The method is very robust and fast and requires less computational power and memory compared to similar approaches and is accurate enough for high level decision making which is vital for robot soccer. Keywords: Global localization, ML, MCL, robot soccer. [ABSTRACT FROM AUTHOR]

Fast and accurate self-localization is one of the most important problems in autonomous mobile robots. In this paper, an analysis by synthesis method is presented for optimizing the self-localization procedure. In the synthesis phase of this method, the robot's observation of the field is predicted using the results of odometry. It is done by calculating the position of the landmarks on the captured image. In the analysis phase, the local search algorithms find the exact position of the landmarks on the image from which the best matching coordinates of the robot are determined using a likelihood function. The final coordinates of the robot are then obtained from the odometry sensor, using an integrated delay compensation and correction technique. Experimental results show that precise and delay-free results are achieved with a very low computational cost. [ABSTRACT FROM AUTHOR]