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Decision-making is an important operation for any autonomous system. Robots in particular must observe their environment and compute appropriate responses. For solitary robots and centralized multiple-robot systems, decision-making is a relatively straightforward operation, since only a single agent (either the solitary robot or the single central controller) is solely responsible for the operation. The problem is much more complex in a decentralized system, to the point where optimal decision-making is intractable in the general case. Decentralized multiple-robot systems (dec-MRS) are robotic teams in which no robot is in authority over any others. The globally observed behaviour of dec-MRS emerges out of the individual robots’ local interactions with each other. This makes system-level decision-making, an operation in which an entire dec-MRS cooperatively makes a decision, a difficult problem. Social insects have long been a source of inspiration for dec-MRS research, and their example is followed in this work. Honeybees and Temnothorax ants must make group decisions in order to choose a new nest site whenever they relocate their colonies. Like the simple robots that compose typical dec-MRS, the insects utilize local, peer-to-peer behaviours to make good, cooperative decisions. This thesis examines their decision-making strategies in detail and proposes a three-phase framework for system-level decision-making by dec-MRS. Two different styles of decision are described, and experiments in both simulation and with real robots were carried out and presented here to demonstrate the framework’s decision-making ability. Using only local, anonymous communication and emergent behaviour, the proposed collective decision-making framework is able to make good decisions reliably, even in the presence of noisy individual sensing. Social cues such as consensus and quorum testing enables the robots to predicate their behaviour during the decision-making process on the global state of their system. Furthermore, because the operations carried out by the individual robots are so simple, and because their complexity to the individual robots is independent of the population size of a dec-MRS, the proposed decision-making framework will scale well to very large population sizes.

Over the past five decades, Autonomous Mobile Robots (AMRs) have been an active research field. Maps of high accuracy are required for AMRs to operate successfully. In addition to this, AMRs needs to localise themselves reliably relative to the map. Simultaneous Localisation and Mapping (SLAM) address the problem of both map building and robot localisation. When exploring large areas, Multi-Robot SLAM (MRSLAM) has the potential to be far more efficient and robust, while sharing the computational burden across robots. However, MRSLAM encounters issues such as difficulty in map fusion of multi-resolution maps, and unknown relative positions of the robots. This thesis describes a distributed multi-resolution map merging algorithm for MRSLAM. HectorSLAM, which is one of many single robot SLAM implementations, has demonstrated exceptional results and was selected as the basis for the MRSLAM implementation in this project. We consider the environment to be three-dimensional with the maps being constrained to a two-dimensional plane. Each robot is equipped with a laser range sensor for perception and has no information regarding the relative positioning of the other robots. The experiments were conducted both in simulation and a real-world environment. Up-to three robots were placed in the same environment with Hector-SLAM running, the local maps and localisation were then sent to a central node, which attempted to find map overlaps and merge the resulting maps. When evaluating the success of the map merging algorithm, the quality of the map from each robot was interrogated. Experiments conducted on up to three AMRs show the effectiveness of the proposed algorithms in an indoor environment.

We present automatic tools for configuring and deploying multi-robot networks of decentralized, mobile robots. These methods are tailored to the decentralized nature of the multi-robot network and the limited information available to each robot. We present methods for determining if user-defined network tasks are feasible or infeasible for the network, considering the limited range of its sensors. To this end, we define rigid and persistent feasibility and present necessary and sufficient conditions (along with corresponding algorithms) for determining the feasibility of arbitrary, user-defined deployments. Control laws for moving multi-robot networks in acyclic, persistent formations are defined. We also present novel Embedded Graph Grammar Systems (EGGs) for coordinating and deploying the network. These methods exploit graph representations of the network, as well as graph-based rules that dictate how robots coordinate their control. Automatic systems are defined that allow the robots to assemble arbitrary, user-defined formations without any reliance on localization. Further, this system is augmented to deploy these formations at the user-defined, global location in the environment, despite limited localization of the network. The culmination of this research is an intuitive software program with a Graphical User Interface (GUI) and a satellite image map which allows users to enter the desired locations of sensors. The automatic tools presented here automatically configure an actual multi-robot network to deploy and execute user-defined network tasks.

As estratégias de mapeamento utilizando múltiplos robôs móveis possuem uma série de vantagens quando comparadas àquelas estratégias baseadas em um único robô. As principais vantagens que podem ser elucidadas são: flexibilidade, ganho de informação e redução do tempo de construção do mapa do ambiente. No presente trabalho, um método de integração de mapas locais é proposto baseado em observações inter-robôs, considerando uma nova abordagem para a exploração do ambiente. Tal abordagem é conhecida como Sistema de Vigilância baseado na Modificação do Sistema Colônias de Formigas, ou IAS-SS. A estratégia IAS-SS é inspirada em mecanismos biológicos que definem a organização social de sistemas de enxames. Especificamente, esta estratégia é baseada em uma modificação do tradicional algoritmo de otimização por colônias de formiga. A principal contribuição do presente trabalho é a adaptação de um modelo de compartilhamento de informações utilizado em redes de sensores móveis, adaptando o mesmo para tarefas de mapeamento. Outra importante contribuição é a colaboração entre o método proposto de integração de mapas e a estratégia de coordenação de múltiplos robôs baseada na teoria de colônias de formigas. Tal colaboração permite o desenvolvimento de uma abordagem de exploração que emprega um mecanismo não físico para depósito e detecção de feromônios em ambientes reais por meio da elaboração do conceito de feromônios virtuais integrados. Resultados obtidos em simulação demonstram que o método de integração de mapas é eficiente, de modo que os ensaios experimentais foram realizados considerando-se um número variável de robôs móveis durante o processo de exploração de ambientes internos com diferentes formas e estruturas. Os resultados obtidos com os diversos experimentos realizados confirmam que o processo de integração é efetivo e adequado para executar o mapeamento do ambiente durante tarefas de exploração e vigilância do mesmo / The multiple robot map building 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 work, a local map integration method is proposed based on the inter-robot observations, considering a recent approach for the environment exploration. This approach is based on the Inverse Ant System-Based Surveillance System strategy, called IASSS. The IAS-SS strategy is inspired on biological mechanisms that define the social organization of swarm systems. Specifically, it is based on a modified version of the known ant colony algorithm. The main contribution of this work is the fit of an information sharing model used in an mobile sensor network, adapting the method for mapping tasks. Another important contribution is the collaboration between the local map integration method and the multiple robot coordination strategy based on ant colony theory. Through this collaboration it is possible to develop an approach that uses a mechanism for controlling the access to pheromones in real environments. Such mechanism is based on the integrated virtual pheromones concept. Simulation results show that the map integration method is efficient, the trials are performed considering a variable number of robots and environments with different structures. Results obtained from several experiments confirm that the integration process is effective and suitable to execute mapping during the exploration task

As estratégias de mapeamento utilizando múltiplos robôs móveis possuem uma série de vantagens quando comparadas àquelas estratégias baseadas em um único robô. As principais vantagens que podem ser elucidadas são: flexibilidade, ganho de informação e redução do tempo de construção do mapa do ambiente. No presente trabalho, um método de integração de mapas locais é proposto baseado em observações inter-robôs, considerando uma nova abordagem para a exploração do ambiente. Tal abordagem é conhecida como Sistema de Vigilância baseado na Modificação do Sistema Colônias de Formigas, ou IAS-SS. A estratégia IAS-SS é inspirada em mecanismos biológicos que definem a organização social de sistemas de enxames. Especificamente, esta estratégia é baseada em uma modificação do tradicional algoritmo de otimização por colônias de formiga. A principal contribuição do presente trabalho é a adaptação de um modelo de compartilhamento de informações utilizado em redes de sensores móveis, adaptando o mesmo para tarefas de mapeamento. Outra importante contribuição é a colaboração entre o método proposto de integração de mapas e a estratégia de coordenação de múltiplos robôs baseada na teoria de colônias de formigas. Tal colaboração permite o desenvolvimento de uma abordagem de exploração que emprega um mecanismo não físico para depósito e detecção de feromônios em ambientes reais por meio da elaboração do conceito de feromônios virtuais integrados. Resultados obtidos em simulação demonstram que o método de integração de mapas é eficiente, de modo que os ensaios experimentais foram realizados considerando-se um número variável de robôs móveis durante o processo de exploração de ambientes internos com diferentes formas e estruturas. Os resultados obtidos com os diversos experimentos realizados confirmam que o processo de integração é efetivo e adequado para executar o mapeamento do ambiente durante tarefas de exploração e vigilância do mesmo / The multiple robot map building 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 work, a local map integration method is proposed based on the inter-robot observations, considering a recent approach for the environment exploration. This approach is based on the Inverse Ant System-Based Surveillance System strategy, called IASSS. The IAS-SS strategy is inspired on biological mechanisms that define the social organization of swarm systems. Specifically, it is based on a modified version of the known ant colony algorithm. The main contribution of this work is the fit of an information sharing model used in an mobile sensor network, adapting the method for mapping tasks. Another important contribution is the collaboration between the local map integration method and the multiple robot coordination strategy based on ant colony theory. Through this collaboration it is possible to develop an approach that uses a mechanism for controlling the access to pheromones in real environments. Such mechanism is based on the integrated virtual pheromones concept. Simulation results show that the map integration method is efficient, the trials are performed considering a variable number of robots and environments with different structures. Results obtained from several experiments confirm that the integration process is effective and suitable to execute mapping during the exploration task

No description available.