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Service robots usually perform repetitive tasks such as collecting garbage, cleaning the house, among others. This kind of robot needs different skills to perform its daily tasks, being people´s recognition a critical skill. One of the techniques used to improve face recognition is padding. The padding technique increases, by a given scale factor, the bounding box of a detected face. In previous work, we had presented a comparative analysis of the influence of the padding in the algorithm used for face recognition. This paper extends the previous analysis by considering the effect of various padding scale factors among different life stages (i.e., toddler, children, teenager, adult, senior, and golden oldie). The result of this analysis shows that increasing the bounding box of detected faces is less efficient for middle-aged people than for younger and elderly people.

Abstract Coordination is an important requirement for most Multiagent Systems. A setplay is a particular instance of a coordinated plan for multi-robot systems in collective sports. Setplays are usually designed by robotics specialists using some existing tools, like the SPlanner, or by hand-coding. This work presents recent improvements to the Strategy Planner (SPlanner) and its corresponding FCPortugal Setplays Framework (FSF) to provide sophisticated setplays. This toolkit is useful to design strategic plans for robotic soccer teams as a particular case of Multi-Agent Systems (MASs). The new enhancements enable more realistic setplays, including, but not limited to, the definition of better pass strategies and defensive setplays. The enhanced tool is used to populate a dataset with demonstrations made by soccer experts and used in a Learning from Demonstration (LfD) approach to allow robotic soccer teams to learn new setplays. A new demonstration mode in the RoboCup Soccer Simulation 3D (SSIM3D) viewer RoboViz was also introduced to integrate this tool with SPlanner. Domain experts can use this set of tools to capture a specific scene in a game in RoboViz and use it as an initial step for a new setplay recommendation in SPlanner. The resulting dataset is organized into fuzzy clusters to be used in a reinforcement learning strategy. This paper describes the whole process. Article Highlights This paper’s main contribution is generating a dataset of setplays to support learning from demonstration in robotic soccer. A set of new features were added to the Strategic Planner(SPlanner) to enable the design of more realistic setplays. The official RoboCup viewer (Roboviz) was integrated with SPlanner using a new demonstration mode.

With the advent of the global and digital world, the number of geographically dispersed firms throughout the world has increased and the problem of Supply Chain (SC) disruption appeared as a main c...

Sustainability management at the production control can make business feasible and profitable, ensuring the safety of the employees, communities and consumers, in addition to the efficient use of resources/raw materials. However, industrial standards do not describe how to deal with sustainability at Productive Systems (PSs) design and their control. Therefore, this paper proposes a framework based on extensions of the ANSI/ISA95 standard for assessment of PSs performance considering sustainability indicators. The framework also considers information processing, storage and access remote for each system component through cyber-physical system and cloud computing technologies. Furthermore, a systematic approach based on Petri Nets (PNs) techniques ensures a formalism to verify and validate the behavior of the Sustainable Productive Systems (SuPSs). Application cases demonstrate and indicate the advantages of the proposed framework to the feasibility, profitability, safety and efficiency of SuPSs.

Multi-Agent Systems (MASs) have been used to solve complex problems that demand intelligent agents working together to reach the desired goals. These Agents should effectively synchronize their individual behaviors so that they can act as a team in a coordinated manner to achieve the common goal of the whole system. One of the main issues in MASs is the agents' coordination, being common domain experts observing MASs execution disapprove agents' decisions. Even if the MAS was designed using the best methods and tools for agents' coordination, this difference of decisions between experts and MAS is confirmed. Therefore, this paper proposes a new dataset schema to support learning the coordinated behavior in MASs from demonstration. The results of the proposed solution are validated in a Multi-Robot System (MRS) organizing a collection of new cooperative plans recommendations from the demonstration by domain experts., Comment: This is a pre-print of an article published in the Journal of Intelligent & Robotic Systems. The final authenticated version will be available online at: https://doi. org/10.1007/s10846-019-01123-w

This paper presents a framework based on Petri Net (PN) and Multi Agent System (MAS) techniques for modeling autonomous multi-robots systems, which require high interaction among the robots (in some cases with humans), synchronization of movements, implementation of cooperation strategies, and a strong notion of the physical environment. The framework considers all phases of the developing process, starting with the abstraction phase and going up to the implementation of the model, to ensure an efficient and flexible approach for specifying the proposed control system architecture. An application example details this solution, in which multi-robots systems can perform tasks and collaborative behaviors considering the cited requirements.

This paper proposes a control architecture for reconfigurable manufacturing systems and its design method based on Petri nets (Input Output Place Transition and Production Flow Schema), Service-Oriented Architecture and Holonic and Multi-Agent System techniques, among other good practices. The control architecture integrates value-added activities, information and resources. The method considers the exchange of knowledge among heterogeneous business workflow of manufacturing subsystems in different geographical locations, and allows modeling process, product, machine and device control. An example demonstrates advantages of the resulting control system.

There is a kind of movement for people to consider sustainability in all their daily activities, not only in the acquisition of goods and services but including the care for health. This induces the emergence of a new business model. Any type of production system (PS) should thus consider sustainability in all its activities and a relationship, which includes not only customers but suppliers, and partners involved from conception, design, manufacturing and provide even service after the use and the disposal of the products. Therefore, an evaluation procedure for PS is proposed to monitor four aspects of sustainability, namely: environmental, social, economical and technological. A framework is considered to deal with the concepts of sustainability and to evaluate performance in industrial PSs considering the indicators to qualify and to quantify their sustainability. It adopts the Petri net technique and extensions of the ANSI/ISA95; Cyber Physical System (CPS) and Smart Grid resources are also considered to treat information processing, storage and access flows by each system component and a Cloud Computing System to connect dispersed PSs. In addition, an evaluation process is systematized to support sustainable PSs by the rational use of production resources and the environment, to guarantee the safety of employees and to maintain the economic profitability of the company, thus, making production processes more efficient.

In a new industrial business model, all aspects of sustainability, i.e. (i) environmental for reduction of negative impacts of using resources, (ii) economic for viability and profitability of business, (iii) social for assuring the safety of employees, communities and consumers, and (iv) technological for efficient and safe use of production resources, need to be effectively incorporated in the productive activities. On the other hand, existing decision-making structures in industries do not explicitly consider how to deal with sustainability indicators when developing a productive system (PS) and its control system. Therefore, this paper discusses the components of a framework and their interactions to apply new concepts to evaluate performance in industrial PSs considering the indicators to qualify and to quantify their sustainability. The framework adopts the Petri net technique and extensions of the ANSI/ISA 95 standard to systemize the evaluation process. This approach assures a formal way to verify and to validate the system sustainability. Besides, the framework considers information processing, storage and access flows between each system component under Cyber Physical System (CPS) and Cloud Computing concepts.

In general, the performance of productive systems considers the efficient use of technological transformation resources (such as machines and raw materials), information processing, and handling/transportation operations. However, there are no normalized criteria or rules to evaluate the performance of a productive system in the context of sustainability. Thus, this paper introduces an approach to identify and evaluate the performance indicators related to the sustainability of productive systems, specifically for geographically dispersed cases, i.e., dispersed productive system (DPS), in which the processes are in a distributed and dispersive architecture. The proposed approach is based on a framework aimed to measure sustainability key performance indicators (SuKPIs) that evaluate the sustainability of a system. The framework considers the ANSI/ISA-95 standard, and the sustainability assessment methodology considers the balance of sustainability indicators, which depend on economic, environmental, social, and technological aspects. The Petri net and derived techniques are used to model and to verify the main functionalities of the proposed framework, and also to monitor the productive processes of DPS for data acquisition of the SuKPIs. An application example is also presented to show the feasibility and validity of the proposal.

A capacidade de reconfiguração de sistemas de manufatura tem sido procurada pelas empresas para assegurar características de agilidade, eficiência e exibilidade para atender as mudanças de tipo/quantidade de produtos, processos, recursos e, além disso, para assegurar a devida reação à ocorrência de falhas. Por outro lado, a Indústria 4.0\" impõe novos desafios para os sistemas de controle, tais como a integração de tecnologias de interação entre homem e máquina em cadeias de valor compondo uma rede de plantas industriais geograficamente dispersas. O controle de sistemas reconfiguráveis de manufatura deve considerar: (i) funcionalidades de sistemas distribuídos e dispersos, tais como agilidade de resposta às mudanças, autonomia e colaboração entre os componentes para alcançar os objetivos do sistema de forma conjunta; (ii) interfaces para sua interoperabilidade e portabilidade; (iii) modularização para facilitar a manutenção, expansão e atualização do sistema, evitando a sobreposição de escopos; e (iv) mecanismos de controle para supervisionar as ações e interações dos componentes, o diagnóstico e a tomada de decisão. O pleno atendimento a estes requisitos não é trivial e formalismos para o desenvolvimento de soluções devem ser adotados. Uma solução é combinar técnicas voltadas para sistema multiagente e holon com arquitetura orientada a serviço através de uma adequada técnica de modelagem usando extensões de rede de Petri: Production Flow Schema e Input Output Place Transition. Portanto, este trabalho prop~oe uma arquitetura de controle e o método de modelagem de seus componentes para sistemas reconfiguráveis de manufatura combinando estas técnicas e considerando os aspectos de personalização, convertibilidade, escalabilidade, modularidade, integrabilidade, diagnosticabilidade, interoperabilidade e colaboração entre os componentes do sistema de controle, inclusive do homem. Um exemplo de aplicação é apresentado para demonstrar a viabilidade da proposta e comprovar os resultados alcançados. The reconfiguration ability of the manufacturing systems has been approached by companies to ensure agility, efficiency and exibility characteristics to address the changes of type/quantity of products, processes and resources and, furthermore, to ensure proper reaction to the fault occurrence. On the other hand, the\"Industry 4.0\" imposes new challenges for control systems, such as interaction between man and machine into value chains composing a network of geographically dispersed industrial plants. The control of reconfigurable manufacturing systems should consider: (i) functionalities requirements of distributed and disperse systems, such as responsiveness to changes, autonomy and collaboration among components to achieve the global system aim; (ii) interfaces for interoperability and portability; (iii) modularity to facilitate maintenance, expansion and upgrade of the system, avoiding the overlapping of scopes; and (iv) control mechanisms to supervise the actions and interactions among components, diagnosis and decision making. The compliance with these requirements is not trivial and formalisms to develop solutions must be adopted. A solution is combining techniques based on holonic and multi-agent system with service-oriented architecture through appropriate modeling using Petri net extensions: Production Flow Schema and Input Output Place Transition. Therefore, this paper proposes control architecture and a method to model components for reconfigurable manufacturing systems, combining these techniques and considering aspects of customization, convertibility, scalability, modularity, integrability, diagnosability, interoperability and collaboration among control system components, including humans. An application example is presented to demonstrate the feasibility of the proposal and verify the results.

Safety is an important issue that has increasingly been focused on. The reasons are the numerous accidents in process industries which require a hard look at current practices such as process design, process control, risk analysis and control, and risk assessment. Critical faults in process industries could lead to loss of lives, environmental damage and significant financial losses of property and equipment. Accidents typically result from the absence or breach of defenses or breach of security restrictions. The so-called defense-in-depth principle embodies the idea of multiple lines of defense and safety barriers along the accident scene; and this principle avoids ensuring the dependence of safety on a single element. Additionally, for several accidents, the identification of concealed faults and/or non observability of critical faults have been reported, during the evolution of faults following the accident, as relevant factors in the occurrence of catastrophic accidents. Finally, as process industries, are complex systems that interact with the environment, the disturbances caused by the environment must be properly diagnosed and treated by these systems. Based on these issues, this work initially proposes a safety control architecture that integrates the concept of reactivity associated with de principles of defense-in-depth, and safety-diagnosability addressing aspects related to critical faults prevention, mitigation and description of the development of failures. We believe that the safety control architecture is a change in paradigm contributing to risk analysis, risk and hazard control, and risk assessment.

This paper presents a method to design a reconfigurable distributed manufacturing control systems which integrates heterogeneous technologies of facilities that are geographically distributed. Due to the heterogeneity of the environment, the method explores concepts of different techniques and takes the best practices from each one. Mechanisms for reconfiguration are proposed using holonic and multi-agent systems techniques. The service-oriented architecture concept is applied to define the interfaces for communication. A combined top-down and bottom- up approach is described using Petri net models. An application example demonstrates the characteristics and advantages of the proposed method, such as autonomy, reactivity, reuse models, interoperability and reconfiguration flexibility.

Productive systems (PS) should currently consider the efficient use of resources (such as technological transformation, handling and material transport) besides the dispersed distribution of productive plants and sustainability concepts to allow the adequate use of environmental resources and reduce costs through local facilities. However, in the literature there are not widely accepted criteria to evaluate this class of Sustainable and Dispersed Productive Systems (SDPS). Therefore, this work introduces a framework for SDPS performance evaluation by extending the system requirements in the ANSI/ISA-95 standard specifications. Petri net (PN) technique and its extension, Production Flow Schema (PFS), are used to systematize the collection of production data and indexes to evaluating the SDPS performance. Cloud computing technology is also considered to provide resources to access information from SDPS. The presented method allows obtaining and choosing the better indicator for sustainable SDPS.

With the advent of globalization, mitigating supply chain disruptions is the differential for any company. However, mitigating supply chain disruption-related risks in companies is a difficult task. There are some ISO norms that provide standards that can make systems to deal with supply chain disruptions and there are some modeling techniques that ensure that supply chain disruptions be mitigated. Although both approaches do not eliminate supply chain disruptions, they have a fundamental importance for supply chain mitigation. In this context, this paper presents an agent-based with the support of some supply chain and risk norms to mitigate supply chain disruptions. The objective of the proposed method is to identify possible hidden supply chain risks, often highlighting previous hidden or overlooked areas of high risk. An example application for a manufacturing firm demonstrates that this model is feasible and can be replicated to different sectors.

Manufacturing systems must necessarily be reconfigurable to assure features of adaptability to unpredictable changes, agility, flexibility and efficiency. The reconfigurable manufacturing system (RMS) has a more adaptable perspective, because it is adjustable to the business and market interests. This reconfigurability systems behavior includes not only information processing but physical transformations and material handling. The reconfigurable manufacturing control system (RMCS) must ensures the system functionalities and the requirements of actual production line, considering the appropriate use of mechatronic and computer-aided technologies. The strategy is to reconfigure the functionality of the system or maintain critical operations so that parts affected by the fault are disabled without affecting other parts of the system. Petri net (PN) is used for description of the system behavior and conversion to a programmable logic controller (PLC) language facilitating the implementation phase, because its advantages as a technique for modeling discrete event system and its similarities to IEC60848 GRAFCET language. Therefore, this paper presents a method for design of RMCS based on PN technique and an application to control a material handling production system.

Available industrial standards do not explicitly consider how to treat sustainability indicators in PS design and its control system. Therefore, this paper proposes a framework to systematize the performance evaluation process for industrial PS considering indicators that qualify and quantify its sustainability. The framework adopts Petri net technique and extensions of the standard ANSI/ISA95. Simulation-based analysis, decision making techniques and a PS´s classification based on product green seal are also considered. Furthermore, the framework considers the processing information, storing and accessing each component using a Cyber Physical Technology due to the trend of PSs to be, in fact, a network for companies that are, in general geographically dispersed.

Building facilities have become important infrastructures for modern productive plants dedicated to services. In this context, the control systems of intelligent buildings have evolved while their reliability has evidently improved. However, the occurrence of faults is inevitable in systems conceived, constructed and operated by humans. Thus, a practical alternative approach is found to be very useful to reduce the consequences of faults. Yet, only few publications address intelligent building modeling processes that take into consideration the occurrence of faults and how to manage their consequences. In the light of the foregoing, a procedure is proposed for the modeling of intelligent building control systems, considersing their functional specifications in normal operation and in the of the event of faults. The proposed procedure adopts the concepts of discrete event systems and holons, and explores Petri nets and their extensions so as to represent the structure and operation of control systems for intelligent buildings under normal and abnormal situations.

Faults occurrence is inevitable in real world and a practical alternative approach is the reduction of fault consequences. Despite of this, the majority of buildings control systems do not have such mechanisms. Thus, this work proposes a procedure for the modeling of control systems for intelligent buildings which considers their functional specifications in normal operation, and in case of faults occurrence. The procedure adopts the concepts of discrete event system, holon, and Petri net and its extensions. It is presented some models derived from case studies, and mechanisms to fault-diagnosis, decision and reconfiguration.

Laser Induced Breakdown Spectroscopy (LIBS) is an advanced analytical technique for elemental determination based on direct measurement of optical emission of excited species on a laser induced plasma. In the realm of elemental analysis, LIBS has great potential to accomplish direct analysis independently of physical sample state (solid, liquid or gas). Presently, LIBS has been easily employed for qualitative analysis, nevertheless, in order to perform quantitative analysis, some effort is still required since calibration represents a difficult issue. Artificial neural network (ANN) is a machine learning paradigm inspired on biological nervous systems. Recently, ANNs have been used in many applications and its classification and prediction capabilities are especially useful for spectral analysis. In this paper an ANN was used as calibration strategy for LIBS, aiming Cu determination in soil samples. Spectra of 59 samples from a heterogenic set of reference soil samples and their respective Cu concentration were used for calibration and validation. Simple linear regression (SLR) and wrapper approach were the two strategies employed to select a set of wavelengths for ANN learning. Cross validation was applied, following ANN training, for verification of prediction accuracy. The ANN showed good efficiency for Cu predictions although the features of portable instrumentation employed. The proposed method presented a limit of detection (LOD) of 2.3 mg dm− 3 of Cu and a mean squared error (MSE) of 0.5 for the predictions.

Soils are an important component in the biogeochemical cycle of carbon, storing about four times more carbon than biomass plants and nearly three times more than the atmosphere. Moreover, the carbon content is directly related on the capacity of water retention, fertility, among other properties. Thus, soil carbon quantification in field conditions is an important challenge related to carbon cycle and global climatic changes. Nowadays, Laser Induced Breakdown Spectroscopy (LIBS) can be used for qualitative elemental analyses without previous treatment of samples and the results are obtained quickly. New optical technologies made possible the portable LIBS systems and now, the great expectation is the development of methods that make possible quantitative measurements with LIBS. The goal of this work is to calibrate a portable LIBS system to carry out quantitative measures of carbon in whole tropical soil sample. For this, six samples from the Brazilian Cerrado region (Argisoil) were used. Tropical soils have large amounts of iron in their compositions, so the carbon line at 247.86 nm presents strong interference of this element (iron lines at 247.86 and 247.95). For this reason, in this work the carbon line at 193.03 nm was used. Using methods of statistical analysis as a simple linear regression, multivariate linear regression and cross-validation were possible to obtain correlation coefficients higher than 0.91. These results show the great potential of using portable LIBS systems for quantitative carbon measurements in tropical soils.

Currently, the design of the manufacturing control systems must assure reconfiguration flexibility for agile reaction to unexpected occurrences in components in the shop-floor control level or business processes in enterprise and factory control levels. Other requirement of these control systems is ensuring collaboration and integration of heterogeneous, autonomous and distributed manufacturing subsystems to take advantages of local facilities. The combination of Holonic and Multi-Agent System HMAS and Service-Oriented Architecture SOA techniques is effective to design this Reconfigurable and Distributed Manufacturing Control System RDMCS. However, there are few methods based on formalisms which ensure a systematic workflow to implement a RDMCS considering since its abstraction phase. Therefore, this paper proposes the use of Petri net in a hybrid bottom-up and top-down design approach to combine HMAS and SOA techniques. Application examples demonstrate the modeling and effectiveness of the proposal using tools for edition, debug, simulation and generation of controller languages from the proposed models.

This paper presents the modeling of fault diagnosis mechanisms extending a method to design reconfigurable and distributed manufacturing control system. The method combines different techniques: service-oriented architecture, holonic and multi-agent system, production flow schema and input-output place-transition Petri net. An application example demonstrates advantages of the proposal, such as at cloud-based engineering, reuse, implementation and reconfiguration flexibility.

The manufacturing control system must immediately react to a variation in product, process specification, fault occurrence, changes in the resources functional capabilities, and other operational factors. Besides, to gain competitive advantage, distributed productive systems must work in cooperation with each other. To effectively integrate these heterogeneous envi-ronments, this paper proposes a method to combine holonic control system, service-oriented architecture and Petri net (PN) techniques. The PN models represent the workflow of the design method itself, the structure and the dynamic of the control system. To demonstrate the advantages of the proposal, an application example of the manufacturing system is described.

Manufacturing control systems must quickly react to variations of product, process specifications, fault occurrence, changes in the resources functional capabilities, and other operational demands. Besides, to gain competitive advantages, dispersed manufacturing systems must cooperate with each other. The combination of holonic control system and service-oriented architecture techniques can be effective to integrate these heterogeneous environments since the agents must also cooperate to achieve their services. Therefore, this paper introduces a service-oriented and holonic control architecture using Petri net to represent the workflow of design method itself, structure and dynamic of the entities. The modeling of an example is presented to demonstrate application at self-organization and adaptation, fault treatment, degeneration, and relatively shorter implementing time.

The adequate evaluation of new technologies in productive systems that perform multiple and simultaneous processes, exploring the intense sharing of resources, demands the updating of supervision and control systems. On the other hand, totally infallible systems are unviable, and for a flexible productive system (FPS) does not to suffer interruptions due to component failure, the concept of AFTCS (active fault-tolerant control system) mechanism must be adopted. In this sense, holonic control system (HCS) is considered a trend for an intelligent automation and the combination of HCS techniques and AFTCS is fundamental to assure efficiency, flexibility and robustness of FPSs. Therefore, this work presents a procedure for the modeling of active holonic fault-tolerant control system (AHFTCS) that considers AFTCS’ requirements and interpreted Petri net for the description of the systems’ behavior. This method is applied to an intelligent building (IB) as a class of FPS and the results are presented.

This work presents recent improvements to Strategy Planner (SPlanner) and its corresponding FCPortugal Setplays Framework (FSF) to provide sophisticated setplays. This toolkit is useful to design strategic plans for robotic soccer teams as a particular case of Multi-Agent Systems (MASs). The new enhancements enable more realistic setplays, including, but not limited to, the definition of better passes strategies and defensive setplays. The enhanced tool is used to populate a dataset with demonstrations made by soccer experts and used in a Learning from Demonstration (LfD) approach to allow teams of robotic soccer learning new setplays.