Information-based search for an atmospheric release using a mobile robot: algorithm and experiments

Finding the location and strength of an unknown hazardous release is of paramount importance in emergency response and environmental monitoring, thus it has been an active research area for several years known as source term estimation. This paper presents a joint Bayesian estimation and planning algorithm to guide a mobile robot to collect informative measurements, allowing the source parameters to be estimated quickly and accurately. The estimation is performed recursively using Bayes’ theorem, where uncertainties in the meteorological and dispersion parameters are considered and the intermittent readings from a low-cost gas sensor are addressed by a novel likelihood function. The planning strategy is designed to maximize the expected utility function based on the estimated information gain of the source parameters. Subsequently, this paper presents the first experimental result of such a system in turbulent, diffusive conditions, in which a ground robot equipped with a low-cost gas sensor responds to the hazardous source stimulated by incense sticks. The experimental results demonstrate the effectiveness of the proposed estimation and search algorithm for source term estimation based on a mobile robot and a low-cost sensor

Modelling for Pest Risk Analysis: Spread and Economic Impacts

The introduction of invasive pests beyond their natural range is one of the main causes of the loss of biodiversity and leads to severe costs. Bioeconomic models that integrate biological invasion spread theory, economic impacts and invasion management would be of great help to increase the transparency of pest risk analysis (PRA) and provide for more effective and efficient management of invasive pests. In this thesis, bioeconomic models of management of invasive pests are developed. The models are applied to three cases of study. The main case looks at the invasion in Europe by the western corn rootworm (WCR), Diabrotica virgifera ssp. virgifera LeConte (Coleoptera: Chrysomelidae). A range of quantitative modelling approaches was employed: (i) dispersal kernels fitted to mark-release-recapture experimental data; (ii) optimal control models combined with info-gap theory; (iii) spatially explicit stochastic simulation models; and (iv) agent-based models. As a result of the application of the models new insights on the management of invasive pests and the links between spread and economic impacts were gained: (i) current official management measures to eradicate WCR were found to be ineffective; (ii) eradication and containment programmes that are economically optimal under no uncertainty were found out to be also the most robustly immune policy to unacceptable outcomes under severe uncertainty; (iii) PRA focusing on single invasive pests might lead to management alternatives that dot not correspond to the optimal economic allocation if the rest of the invasive pests sharing the same management budget are considered; (iv) the control of satellite colonies of an invasion occurring by stratified dispersal is ineffective when a strong propagule pressure is generated from the main body of the invasion and this effect is increased by the presence of human-assisted long-distance dispersal; and (v) agent-based models were shown to be an adequate tool to integrate biological invasion spread models with economic analysis models

Coalition based approach for shop floor agility – a multiagent approach

Dissertation submitted for a PhD degree in Electrical Engineering, speciality of Robotics and Integrated Manufacturing from the Universidade Nova de Lisboa, Faculdade de Ciências e TecnologiaThis thesis addresses the problem of shop floor agility. In order to cope with the disturbances and uncertainties that characterise the current business scenarios faced by manufacturing companies, the capability of their shop floors needs to be improved quickly, such that these shop floors may be adapted, changed or become easily modifiable (shop floor reengineering). One of the critical elements in any shop floor reengineering process is the way the control/supervision architecture is changed or modified to accommodate for the new processes and equipment. This thesis, therefore, proposes an architecture to support the fast adaptation or changes in the control/supervision architecture. This architecture postulates that manufacturing systems are no more than compositions of modularised manufacturing components whose interactions when aggregated are governed by contractual mechanisms that favour configuration over reprogramming. A multiagent based reference architecture called Coalition Based Approach for Shop floor Agility – CoBASA, was created to support fast adaptation and changes of shop floor control architectures with minimal effort. The coalitions are composed of agentified manufacturing components (modules), whose relationships within the coalitions are governed by contracts that are configured whenever a coalition is established. Creating and changing a coalition do not involve programming effort because it only requires changes to the contract that regulates it

Operation and Planning of Energy Hubs Under Uncertainty - a Review of Mathematical Optimization Approaches

Co-designing energy systems across multiple energy carriers is increasingly attracting attention of researchers and policy makers, since it is a prominent means of increasing the overall efficiency of the energy sector. Special attention is attributed to the so-called energy hubs, i.e., clusters of energy communities featuring electricity, gas, heat, hydrogen, and also water generation and consumption facilities. Managing an energy hub entails dealing with multiple sources of uncertainty, such as renewable generation, energy demands, wholesale market prices, etc. Such uncertainties call for sophisticated decision-making techniques, with mathematical optimization being the predominant family of decision-making methods proposed in the literature of recent years. In this paper, we summarize, review, and categorize research studies that have applied mathematical optimization approaches towards making operational and planning decisions for energy hubs. Relevant methods include robust optimization, information gap decision theory, stochastic programming, and chance-constrained optimization. The results of the review indicate the increasing adoption of robust and, more recently, hybrid methods to deal with the multi-dimensional uncertainties of energy hubs

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available

ProCLAIM: an argument-based model for deliberating over safety critical actions

In this Thesis we present an argument-based model – ProCLAIM – intended to provide a setting for heterogeneous agents to deliberate on whether a proposed action is safe. That is, whether or not a proposed action is expected to cause some undesirable side effect that will justify not to undertake the proposed action. This is particularly relevant in safetycritical environments where the consequences ensuing from an inappropriate action may be catastrophic. For the practical realisation of the deliberations the model features a mediator agent with three main tasks: 1) guide the participating agents in what their valid argumentation moves are at each stage of the deliberation; 2) decide whether submitted arguments should be accepted on the basis of their relevance; and finally, 3) evaluate the accepted arguments in order to provide an assessment on whether the proposed action should or should not be undertaken, where the argument evaluation is based on domain consented knowledge (e.g guidelines and regulations), evidence and the decision makers’ expertise. To motivate ProCLAIM’s practical value and generality the model is applied in two scenarios: human organ transplantation and industrial wastewater. In the former scenario, ProCLAIM is used to facilitate the deliberation between two medical doctors on whether an available organ for transplantation is or is not suitable for a particular potential recipient (i.e. whether it is safe to transplant the organ). In the later scenario, a number of agents deliberate on whether an industrial discharge is environmentally safe.En esta tesis se presenta un modelo basado en la Argumentación –ProCLAIM– cuyo n es proporcionar un entorno para la deliberación sobre acciones críticas para la seguridad entre agentes heterogéneos. En particular, el propósito de la deliberación es decidir si los efectos secundario indeseables de una acción justi can no llevarla a cabo. Esto es particularmente relevante en entornos críticos para la seguridad, donde las consecuencias que se derivan de una acción inadecuada puede ser catastró cas. Para la realización práctica de las deliberaciones propuestas, el modelo cuenta con un agente mediador con tres tareas principales: 1) guiar a los agentes participantes indicando cuales son las líneas argumentación válidas en cada etapa de la deliberación; 2) decidir si los argumentos presentados deben ser aceptadas sobre la base de su relevancia y, por último, 3) evaluar los argumentos aceptados con el n de proporcionar una valoración sobre la seguridad de la acción propuesta. Esta valoración se basa en guías y regulaciones del dominio de aplicación, en evidencia y en la opinión de los expertos responsables de la decisión. Para motivar el valor práctico y la generalidad de ProCLAIM, este modelo se aplica en dos escenarios distintos: el trasplante de órganos y la gestión de aguas residuales. En el primer escenario el modelo se utiliza para facilitar la deliberación entre dos médicos sobre la viabilidad del transplante de un órgano para un receptor potencial (es decir, si el transplante es seguro). En el segundo escenario varios agentes deliberan sobre si los efectos de un vertido industrial con el propósito de minimizar su impacto medioambiental