An overview of RoboCup-2002 Fukuoka/Busan

© 2003, American Association for Artificial Intelligence (AAAI). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/This article reports on the Sixth Robot World Cup Competition and Conference (RoboCup-2002) Fukuoka/Busan, which took place from 19 to 25 June in Fukuoka, Japan. It was the largest RoboCup since 1997 and held the first humanoid league competition in the world. Further, the first ROBOTREX (robot trade and exhibitions) was held with about 50 companies, universities, and institutes represented. A total of 117,000 spectators witnessed this marvelous event, To the best of our knowledge, this was the largest robotic event in history.Peer reviewe

Distributed agent-based building evacuation simulator

The optimisation of the evacuation of a building plays a fundamental role in emergency situations. The behaviour of individuals, the directions that civilians receive, and the actions of the emergency personnel, will affect the success of the operation. We describe a simulation system that represents the individual, intelligent, and interacting agents that cooperate and compete while evacuating the building. The system also takes into account detailed information about the building and the sensory capabilities that it may contain. Since the level of detail represented in such a simulation can lead to computational needs that grow at least as a polynomial function of the number of the simulated agents, we propose an agent-oriented Distributed Building Evacuation Simulator (DBES). The DBES is integrated with a wireless sensor network which offers a closed loop representation of the evacuation procedure, including the sensed data and the emergency decision making

A Constraint-Based Model for Fast Post-Disaster Emergency Vehicle Routing

Disasters like terrorist attacks, earthquakes, hurricanes, and volcano eruptions are usually unpredictable events that affect a high number of people. We propose an approach that could be used as a decision support tool for a post-disaster response that allows the assignment of victims to hospitals and organizes their transportation via emergency vehicles. By exploiting the synergy between Mixed Integer Programming and Constraint Programming techniques, we are able to compute the routing of the vehicles so as to rescue much more victims than both heuristic based and complete approaches in a very reasonable time

On localisation with robust power control for safety critical wireless sensor networks

A hybrid methodology is proposed for use in low power, safety critical wireless sensor network applications, where quality-of-service orientated transceiver output power control is required to operate in parallel with radio frequency-based localization. The practical implementation is framed in an experimental procedure designed to track a moving agent in a realistic indoor environment. An adaptive time synchronized approach is employed to ensure the positioning technique can operate effectively in the presence of dataloss and where the transmitter output power of the mobile agent is varying due to power control. A deterministic multilateration-based positioning approach is adopted and accuracy is improved by filtering signal strength measurements overtime to account for multipath fading. The location estimate is arrived at by employing least-squares estimation. Power control is implemented at two separate levels in the network topology. First, power control is applied to the uplink between the tracking reference nodes and the centralized access point. A number of algorithms are implemented highlighting the advantage associated with using additional feedback bandwidth, where available, and also the need for effective time delay compensation. The second layer of power control is implemented on the uplink between the mobile agent and the access point and here quantifiable improvements in quality of service and energy efficiency are observed. The hybrid paradigm is extensively tested experimentally on a fully compliant 802.15.4 testbed, where mobility is considered in the problem formulation using a team of fully autonomous robots.A hybrid methodology is proposed for use in low power, safety critical wireless sensor network applications, where quality-of-service orientated transceiver output power control is required to operate in parallel with radio frequency-based localization. The practical implementation is framed in an experimental procedure designed to track a moving agent in a realistic indoor environment. An adaptive time synchronized approach is employed to ensure the positioning technique can operate effectively in the presence of dataloss and where the transmitter output power of the mobile agent is varying due to power control. A deterministic multilateration-based positioning approach is adopted and accuracy is improved by filtering signal strength measurements overtime to account for multipath fading. The location estimate is arrived at by employing least-squares estimation. Power control is implemented at two separate levels in the network topology. First, power control is applied to the uplink between the tracking reference nodes and the centralized access point. A number of algorithms are implemented highlighting the advantage associated with using additional feedback bandwidth, where available, and also the need for effective time delay compensation. The second layer of power control is implemented on the uplink between the mobile agent and the access point and here quantifiable improvements in quality of service and energy efficiency are observed. The hybrid paradigm is extensively tested experimentally on a fully compliant 802.15.4 testbed, where mobility is considered in the problem formulation using a team of fully autonomous robots

Genetic programming for the RoboCup Rescue Simulation System

The Robocup Rescue Simulation System (RCRSS) is a dynamic system of multi-agent interaction, simulating a large-scale urban disaster scenario. Teams of rescue agents are charged with the tasks of minimizing civilian casualties and infrastructure damage while competing against limitations on time, communication, and awareness. This thesis provides the first known attempt of applying Genetic Programming (GP) to the development of behaviours necessary to perform well in the RCRSS. Specifically, this thesis studies the suitability of GP to evolve the operational behaviours required of each type of rescue agent in the RCRSS. The system developed is evaluated in terms of the consistency with which expected solutions are the target of convergence as well as by comparison to previous competition results. The results indicate that GP is capable of converging to some forms of expected behaviour, but that additional evolution in strategizing behaviours must be performed in order to become competitive. An enhancement to the standard GP algorithm is proposed which is shown to simplify the initial search space allowing evolution to occur much quicker. In addition, two forms of population are employed and compared in terms of their apparent effects on the evolution of control structures for intelligent rescue agents. The first is a single population in which each individual is comprised of three distinct trees for the respective control of three types of agents, the second is a set of three co-evolving subpopulations one for each type of agent. Multiple populations of cooperating individuals appear to achieve higher proficiencies in training, but testing on unseen instances raises the issue of overfitting

AFRANCI : multi-layer architecture for cognitive agents

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 201

RoboCup rescue : development of inteligent cooperative agents

Mestrado em Engenharia de Computadores e TelemáticaO trabalho desenvolvido nesta dissertação tem como tema o desenvolvimento de um agente inteligente com coordenação e comunicação no ambiente RoboCup Rescue. No RoboCup Rescue existem seis tipos de agentes, no entanto nesta tese só dois agentes foram desenvolvidos, especificamente o tipo de agentes Ambulâncias e Centros de Ambulâncias. O tipo de agente Ambulância é o elemento responsável pelo salvamento de civis na cidade virtual que constitui o ambiente RoboCup Rescue. Para cumprir essa tarefa da forma mais eficiente possível conta com coordenação e comunicação com outros agentes do mesmo tipo, e com os Centros de Ambulâncias. O comportamento da ambulância é modelado tanto para situações em que o Centro de Ambulâncias está presente durante a simulação, podendo, portanto, delegar funções para o Centro; como em situações em que o Centro não está presente, e, por isso, as ambulâncias estão encarregues de todo o processamento dos dados e de todas as tomadas de decisões. As actividades desenvolvidas pelas ambulâncias podem ser resumidas a duas: pesquisa e salvamento. Para a primeira as soluções passam muito pelo uso de algoritmos estudados em Teoria de Grafos, já que a cidade virtual é, na sua essência, um grafo, e são necessárias soluções para problemas como visitar o mapa completamente e determinar o caminho mais rápido entre dois nós. Na parte de salvamento a coordenação tem um grande papel a desempenhar.É necessário determinar que ambulâncias devem ir socorrer que civil, e quantas ambulâncias devem ajudar; ou que ambulâncias que devem continuar com a pesquisa do mapa. Ou seja, a coordenação é vital para uma utilização eficiente dos recursos disponíveis, e, consequentemente, uma boa pontuação. ABSTRACT: The work developed in this thesis has as background the development of an intelligent agent with coordination and communication in the environment of the RoboCup Rescue. RoboCup Rescue has six types of agents, however only two were developed in this thesis, specifically Ambulances and Ambulance Centers. The type of agent Ambulance is the element responsable for the rescuing of civilians in the virtual city which comprises the environment of RoboCup Rescue. To fulfill this task in the most efficient way possible it relies on coordination and communication with other agents of the same type, as well as Ambulance Centers. The behavior of an ambulance is modeled for situations when an Ambulance Center is available during the simulation, thus allowing the ambulances the possibility of dividing some of the processing and decision making; or, for situations when a center is not available and it is up to the ambulances to do make all of the decisions, and do all of the processing. The activities performed by the ambulances can be summarized in two: search, and rescue. For the first, many of the solutions may be provided by algorithms studied in Graph Theory, since the virtual city is, in its essence, a graph, and its necessary solutions to problems such as visit the city entirely, and determine the shortest path between two locations, or nodes. In the rescuing part, the coordination has a very big part to play. It is necessary to choose which ambulances should rescue a civilian, and how many should help doing it; or, which ambulances should continue searching the city for more civilians. In other words, coordination is vital for an efficient allocation of available resources, and, ultimately, a good score