Catálogo de publicaciones - libros

This paper proposes a novel approach for a Constructive Self-Organizing Map (SOM) based world modeling for search and rescue operations in disaster environments. In our approach, nodes of the self organizing network consist of victim and waypoint classes where victim denotes a human being waiting to be rescued and waypoint denotes a free space that can be reached from the entrance of debris. The proposed approach performed better than traditional self-organizing maps in terms of both the accuracy of the output and the learning speed. In this paper the detailed explanation of the approach and some experimental results are given.

The RoboCupRescue Simulation project aims at simulating large-scale disasters in order to explore coordination strategies for real-life rescue missions. This can only be achieved if the simulation itself is as close to reality as possible. In this paper, we present a new fire simulator based on a realistic physical model of heat development and heat transport in urban fires. It allows to simulate three different ways of heat transport (radiation, convection, direct transport) and the influence of wind. The protective effects of spraying water on non-burning buildings is also simulated, thus allowing for more strategic and precautionary behavior of rescue agents. Our experiments showed the simulator to create realistic fire propagations both with and without influence of fire brigade agents.

We address the problem of merging multiple noisy maps in the rescue environment. The problem is tackled by performing a stochastic search in the space of possible map transformations, i.e. rotations and translations. The proposed technique, which performs a time variant Gaussian random walk, turns out to be a generalization of other search techniques like hill-climbing or simulated annealing. Numerical examples of its performance while merging partial maps built by our rescue robots are provided.

Orpheus mobile robot is a teleoperated device primarily designed for remote exploration of hazardous places and rescue missions. The robot is able to operate both indoors and outdoors, is made to be durable and reliable. The robot is remotely operated with help of visual telepresence. The device is controlled through advanced user interface with joystick and head mounted display with inertial head movement sensor. The functionality and reliability of the system was tested on Robocup Rescue League 2003 world championship in Italy where our team placed on 1st place.

In this paper, the problem of determining if a population of mobile robots is able to travel from an initial configuration to a target configuration is addressed. This problem is related with the controllability of the automaton describing the system. To solve the problem, the concept of navigation automaton is introduced, allowing a simplification in the analysis of controllability. A set of illustrative examples is presented.

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.

This paper introduces a general formulation of relational behaviours for cooperative real robots and an example of its implementation using the pass between soccer robots of the Middle-Sized League of RoboCup. The formulation is based on the Joint Commitment Theory and the pass implementation is supported by past work on soccer robots navigation. Results of experiments with real robots under controlled situations (i.e., not during a game) are presented to illustrate the described concepts.

In this paper we focus on plan execution in highly dynamic environments. Our plan execution procedure is part of a high-level planning system which controls the actions of our RoboCup team ”Mostly Harmless”. The used knowledge representation scheme is based on traditional STRIPS planning and qualitative reasoning principles. In contrast to other plan execution algorithms we introduce the concept of plan invariants which have to be fulfilled during the whole plan execution cycle. Plan invariants aid robots in detecting problems as early as possible. Moreover, we demonstrate how the approach can be used to achieve cooperative behavior.

We are exploring the use of auction mechanisms to assign roles within a team of agents operating in a dynamic environment. Depending on the degree of collaboration between the agents and the specific auction policies employed, we can obtain varying combinations of role assignments that can affect both the speed and the quality of task execution. In order to examine this extremely large set of combinations, we have developed a theoretical framework and an environment in which to experiment and evaluate the various options in policies and levels of collaboration. This paper describes our framework and experimental environment. We present results from examining a set of representative policies within our test domain — a high-level simulation of the RoboCup four-legged league soccer environment.

Object recognition systems contain a large amount of highly specific knowledge tailored to the objects in the domain of interest. Not only does the system require information for each object in the recognition process, it may require entirely different vision processing techniques. Generic programming for vision processing tasks is hard since systems on-board a mobile robots have strong performance requirements. Such issues as keeping up with incoming frames from a camera limit the layers of abstraction that can be applied. This results in software that is customized to the domain at hand, that is difficult to port to other applications and that is not particularly robust to changes in the visual environment.

In this paper we describe a high level object definition language that removes the domain specific knowledge from the implementation of the object recognition system. The language has features of object-orientation and logic, being more declarative and less imperative. We present an implementation of the language efficient enough to be used on a Sony AIBO in the Robocup Four-Legged league competition and several illustrations of its use to rapidly adjust to new environments through quickly crafted object definitions.