Janderson R. Oliveira

A distributed, bio-inspired coordination strategy for multiple agent systems applied to surveillance tasks in unknown environments

Multiple agent systems are applied to exploration and surveillance tasks. A new distributed coordination strategy, designed according to a modified version of the artificial ant system, is described. The strategy is able to adapt the current system dynamics if the number of robots or the environment structure or both change. Experiment simulations are executed to evaluate two versions of the strategy considering different multiple robot systems and environment structures. Results confirm that exploration and surveillance general behaviors emerge from the individual agent behavior. Different compiled data sets are considered to assess the strategies, namely: needed time to conclude the task; and time between two consecutive sensory on a specific region. The results show that the strategy is effective and relatively efficient to execute the exploration and surveillance tasks.

Parametric investigation of a distributed strategy for multiple agents systems applied to cooperative tasks

Distributed coordination strategy based on modified version of the artificial ant system directs mobile robots to unexplored regions and regions that were not recently explored for accomplishing cooperative tasks as exploration and surveillance. Previously, application of the strategy confirmed that exploration and surveillance general behaviors emerge from the individual agent behavior. The strategy is able to adapt the current system dynamics if the number of robots or the environment structure or both change. In this paper, parametric variation of strategy is executed according to pheromone evaporation and releasing phenomena. Experiment results demonstrate that different configurations of phenomenon affect exploration and surveillance behaviors. Different compiled data sets are considered to assess the strategies, namely: needed time to conclude the task; and time between two consecutive sensory on a specific region. The results show that there is a set of configuration of the phenomena to become the strategy more efficient to execute the exploration and surveillance tasks.

Image skeletonization method applied to generation of topological maps

The environment mapping has been a great challenge of many researchers of the mobile robot autonomous navigation area. There are two important paradigms for mapping, metric and topological mapping. Several methods that combine the advantages of each paradigm have been proposed. Thereby the aim of this work is to provide an alternative hybrid approach, simple and efficient, for the construction of topological maps in indoor environments. For this, the proposal is the combination of two techniques found in the literature, one of them is a technique known as Occupation Grid, and the other is an image skeletonization method used here for topological mapping. Several experiments have been performed for verifying the efficiency of the proposed approach. The results obtained by junction of these two techniques demonstrate that image skeletonization technique is simple and feasible for obtaining the topological lines corresponding to free space of the environment.

Integration of virtual pheromones for mapping/exploration of environments by using multiple robots

The multiple robot coordination strategies have several advantages when compared to strategies based on a single robot, in terms of flexibility, gain of information and reduction of map building time. In this paper, a local pheromone map integration method is proposed based on the inter-robot observations, considering a method for the environment exploration named the Inverse Ant System-Based Surveillance System strategy (IAS-SS). Simulation results show that the map integration method is efficient, the trials are performed considering a variable number of robots in an indoor environment. Results obtained from several experiments confirm that the integration process is effective and suitable to execute the control of the access to pheromones in a virtual way.

Estratégia de Formação Auto-adaptativa Baseada em uma Modificação do Algoritmo ACO

Resumo—Neste trabalho é proposta uma estratégia para coordenação de um sistema com múltiplos robôs aplic ado a tarefas em que a formação é uma característica esse ncial requerida. O projeto da estratégia é inspirado em mecanismos biológicos que definem a organização social de sist emas coletivos, especificamente, sistemas de colônias de formigas. Diagramas de Voronoi e triangularização de Delaunay são outras t écnicas utilizadas para modelar a estratégia. A estratégia se adapta a diversos cenários, nos quais a estrutura do ambient e muda. O desempenho do sistema de coordenação é avaliado uti lizando-se um simulador. A estratégia é flexível e robusta em relação ao ambiente, adaptando a topologia do grupo quando nec ssário. Tarefas de mapeamento do ambiente podem ser eficient mente executadas, independentemente da configuração do am biente ou dos obstáculos presentes no mesmo.

Uma Estratégia de Coordenação Distribuída e Bio-Inspirada para Sistema Multiagentes Aplicada à Tarefa de Vigilância em Ambientes Desconhecidos

A new distributed coordination strategy, designed according to a modified version of the artificial ant system, is described. The strategy is able to adapt the current system dynamics if the number of robots or the environment structure or both change. Experiment simulations are executed to evaluate two versions of the strategy considering different multiple robot systems and environment structures. Results confirm that exploration and surveillance general behaviors emerge from the individual agent behavior. Needed time to conclude the task and the period of time between two consecutive sensory on a specific region are parameters to evaluate the strategy. The results show that the strategy is effective and efficient to execute the cooperative tasks.

Mathematical morphology filters applied to an image skeletonization method to generation of topological maps

The environment mapping has been a great challenge of many researchers of the mobile robot autonomous navigation area. There are two important paradigms for mapping, metric and topological mapping. Diverse mapping methods that combine the advantages of each paradigm have been proposed. A simple alternative is to combine the metric mapping technique known as Occupancy Grid with an image skeletonization method to topological mapping. However, due noises inherent to the own robot ability of capturing sensor signals, the topological map generated through this combination presents several unnecessary topological lines, hindering consequently the task of autonomous navigation. Therefore, the aim of this work is to propose a set of mathematical morphology filters to generation of topological maps suitable for real environments, seeking to reduce influence of noises in performed mapping. Several experiments have been performed to verify the efficiency of the proposed approach. The application this mathematical morphology filters demonstrated to be an useful method to the creation of topological maps free of noises.