Second Workshop on Modelling of Objects, Components and Agents

This report contains the proceedings of the workshop Modelling of Objects, Components, and Agents (MOCA'02), August 26-27, 2002.The workshop is organized by the 'Coloured Petri Net' Group at the University of Aarhus, Denmark and the 'Theoretical Foundations of Computer Science' Group at the University of Hamburg, Germany. The homepage of the workshop is: http://www.daimi.au.dk/CPnets/workshop02

An agile and adaptive holonic architecture for manufacturing control

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. 2004. Faculdade de Engenharia. Universidade do Port

Multi-robot Motion Planning based on Nets-within-Nets Modeling and Simulation

This paper focuses on designing motion plans for a heterogeneous team of robots that has to cooperate in fulfilling a global mission. The robots move in an environment containing some regions of interest, and the specification for the whole team can include avoidances, visits, or sequencing when entering these regions of interest. The specification is expressed in terms of a Petri net corresponding to an automaton, while each robot is also modeled by a state machine Petri net. With respect to existing solutions for related problems, the current work brings the following contributions. First, we propose a novel model, denoted {High-Level robot team Petri Net (HLPN) system, for incorporating the specification and the robot models into the Nets-within-Nets paradigm. A guard function, named Global Enabling Function (gef), is designed to synchronize the firing of transitions such that the robot motions do not violate the specification. Then, the solution is found by simulating the HPLN system in a specific software tool that accommodates Nets-within-Nets. An illustrative example based on a Linear Temporal Logic (LTL) mission is described throughout the paper, complementing the proposed rationale of the framework.Comment: submitted to 62nd IEEE Conference on Decision and Control, Dec. 13-15, 202

Modeling Supervisory Control in Multi Robot Applications

We consider multi robot applications, where a human operator monitors and supervise the team to pursue complex objectives in complex environments. Robots, specially at field sites, are often subject to unexpected events that can not be managed without the intervention of the operator(s). For example, in an environmental monitoring application, robots might face extreme environmental events (e.g. water currents) or moving obstacles (e.g. animal approaching the robots). In such scenarios, the operator often needs to interrupt the activities of individual team members to deal with particular situations. This work focuses on human-multi-robot-interaction in these casts. A widely used approach to monitor and supervise robotic teams are team plans, which allow an operator to interact via high level objectives and use automation to work out the details. The first problem we address in this context, is how human interrupts (i.e. change of action due to unexpected events) can be handled within a robotic team. Typically, after such interrupts, the operator would need to restart the team plan to ensure its success. This causes delays and imposes extra load on the operator. We address this problem by presenting an approach to encoding how interrupts can be smoothly handled within a team plan. Building on a team plan formalism that uses Colored Petri Nets, we describe a mechanism that allows a range of interrupts to be handled smoothly, allowing the team to effectively continue with its task after the operator intervention. We validate the approach with an application of robotic water monitoring. Our experiments show that the use of our interrupt mechanism decreases the time to complete the plan (up to 48% reduction) and decreases the operator load (up to 80% reduction in number of user actions). Moreover, we performed experiments with real robotic platforms to validate the applicability of our mechanism in the actual deployment of robotic watercraft. The second problem we address is how to handle intervention requests from robots to the operator. In this case, we consider autonomous robotic platforms that are able to identify their situation and ask for the intervention of the operator by sending a request. However, large teams can easily overwhelm the operator with several requests, hence hindering the team performance. As a consequence, team members will have to wait for the operator attention, and the operator becomes a bottleneck for the system. Our contribution in this context is to make the robots learn cooperative strategies to best utilize the operator's time and decrease the idle time of the robotic system. In particular, we consider a queuing model (a.k.a balking queue), where robots decide whether or not to join the queue. Such decisions are computed by considering dynamic features of the system (e.g. the severity of the request, number of requests, etc.). We examine several decision making solutions for computing these cooperative strategies, where our goal is to find a trade-off between lower idle time by joining the queue and fewer failures due to the risk of not joining the queue. We validate the proposed approaches in a simulation robotic water monitoring application. The obtained results show the effectiveness of our proposed models in comparison to the queue without balking, when considering team reward and total idle time

An agile and adaptive holonic architecture for manufacturing control

In the last decades significant changes in the manufacturing environment have been noticed: moving from a local economy towards a global economy, with markets asking for products with high quality at lower costs, highly customised and with short life cycle. In this environment, the manufacturing enterprises, to avoid the risk to lose competitiveness, search to answer more closely to the customer demands, by improving their flexibility and agility, while maintaining their productivity and quality. Actually, the dynamic response to emergence is becoming a key issue, due to the weak response of the traditional manufacturing control systems to unexpected disturbances, mainly because of the rigidity of their control architectures. In these circumstances, the challenge is to develop manufacturing control systems with autonomy and intelligence capabilities, fast adaptation to the environment changes, more robustness against the occurrence of disturbances, and easier integration of manufacturing resources and legacy systems. Several architectures using emergent concepts and technologies have been proposed, in particular those based in the holonic manufacturing paradigm. Holonic manufacturing is a paradigm based in the ideas of the philosopher Arthur Koestler, who proposed the word holon to describe a basic unit of organisation in biological and social systems. A holon, as Koestler devised the term, is an identifiable part of a (manufacturing) system that has a unique identity, yet is made up of sub-ordinate parts and in turn is part of a larger whole. The introduction of the holonic manufacturing paradigm allows a new approach to the manufacturing problem, bringing the advantages of modularity, decentralisation, autonomy, scalability, and re-use of software components. This dissertation intends to develop an agile and adaptive manufacturing control architecture to face the current requirements imposed to the manufacturing enterprises. The architecture proposed in this dissertation addresses the need for the fast reaction to disturbances at the shop floor level, increasing the agility and flexibility of the enterprise, when it works in volatile environments, characterised by the frequent occurrence of unexpected disturbances. The proposed architecture, designated by ADACOR (ADAptive holonic COntrol aRchitecture for distributed manufacturing systems), is based in the holonic manufacturing paradigm, build upon autonomous and cooperative holons, allowing the development of manufacturing control applications that present all the features of decentralised and holonic systems. ADACOR holonic architecture introduces an adaptive control that balances dynamically between a more centralised structure and a more decentralised one, allowing to combine the global production optimisation with agile reaction to unexpected disturbances. Nas últimas décadas têm-se assistido a mudanças significativas no ambiente de fabrico: evoluindo de uma economia local para um economia global, com os mercados a procurar produtos com elevada qualidade a baixos preços, altamente customizados e com um ciclo de vida curto. Neste ambiente, as empresas de manufactura, para evitar o risco de perda de competitividade, procuram responder às solicitações dos clientes, melhorando a sua flexibilidade e agilidade, mantendo os mesmos índices de produtividade e qualidade. Na verdade, a resposta dinâmica à emergência está a tornar-se num assunto chave, devido `a fraca resposta a perturbações que os sistemas de controlo de fabrico tradicionais apresentam, principalmente devido à rigidez das suas arquitecturas de controlo. Nestas circunstâncias, é fundamental o desenvolvimento de sistemas de controlo de fabrico com capacidades de autonomia e inteligência, rápida adaptação às mudanças, maior robustez à ocorrência de perturbações e fácil integração de recursos físicos e sistemas legados. Diversas arquitecturas usando conceitos e tecnologias emergentes têm sido propostas, em particular algumas baseadas no paradigma da produção holónica. O paradigma da produção holónica é inspirado nas ideias de Arthur Koestler, que propôs a palavra holon para descrever uma unidade básica de organização de sistemas biológicos e sociais. Um holon, de acordo com a definição de Koestler, é uma parte identificável do sistema com identidade única, composta por sub-partes e fazendo simultaneamente parte do todo. A introdução do paradigma da produção holónica permite uma nova abordagem aos sistemas de controlo de fabrico, trazendo vantagens de modularidade, descentralização, autonomia, escalabilidade e reutilização de componentes. Esta dissertação pretende desenvolver uma arquitectura de controlo ágil e adaptativa que suporte os requisitos actuais impostos `as empresas de manufactura. A arquitectura proposta visa a necessidade de uma reacção rápida a perturbações, ao nível da planta fabril, melhorando a flexibilidade e agilidade da empresa quando esta opera em ambientes voláteis, caracterizados pela ocorrência frequente de perturbações inesperadas. A arquitectura proposta, designada por ADACOR (ADAptive holonic COntrol aRchitecture for distributed manufacturing systems), é baseada no paradigma da produção holónica e construída sobre holons autónomos e cooperativos, permitindo o desenvolvimento de aplicações de controlo de fabrico que apresentem todas as características dos sistemas descentralizados e holónicos. A arquitectura holónica ADACOR introduz um controlo adaptativo que balança dinamicamente entre uma estrutura de controlo mais centralizada e uma mais descentralizada, permitindo combinar a optimização da produção com a ágil reacção a perturbações

A framework for smart production-logistics systems based on CPS and industrial IoT

Industrial Internet of Things (IIoT) has received increasing attention from both academia and industry. However, several challenges including excessively long waiting time and a serious waste of energy still exist in the IIoT-based integration between production and logistics in job shops. To address these challenges, a framework depicting the mechanism and methodology of smart production-logistics systems is proposed to implement intelligent modeling of key manufacturing resources and investigate self-organizing configuration mechanisms. A data-driven model based on analytical target cascading is developed to implement the self-organizing configuration. A case study based on a Chinese engine manufacturer is presented to validate the feasibility and evaluate the performance of the proposed framework and the developed method. The results show that the manufacturing time and the energy consumption are reduced and the computing time is reasonable. This paper potentially enables manufacturers to deploy IIoT-based applications and improve the efficiency of production-logistics systems

Object-Oriented Simulator of Multi-Agent System for Temporally Rich Domains

An object-oriented implementation of a program simulator for a multi-agent system (MAS) is described. The model of a MAS is hierarchical model, consisting of different levels, where each level contains clusters of agents. A paradigm of a blackboard is used for communication among agents, clusters, as well as levels. The Petri Nets with Time Tokens are used as a basic concept for this model. An example of the use of the object-oriented simulator in a dynamic scene analysis is given

Reasoning about Goal-Plan Trees in Autonomous Agents: Development of Petri net and Constraint-Based Approaches with Resulting Performance Comparisons

Multi-agent systems and autonomous agents are becoming increasingly important in current computing technology. In many applications, the agents are often asked to achieve multiple goals individually or within teams where the distribution of these goals may be negotiated among the agents. It is expected that agents should be capable of working towards achieving all its currently adopted goals concurrently. However, in doing so, the goals can interact both constructively and destructively with each other, so a rational agent must be able to reason about these interactions and any other constraints that may be imposed on them, such as the limited availability of resources that could affect their ability to achieve all adopted goals when pursuing them concurrently. Currently, agent development languages require the developer to manually identify and handle these circumstances. In this thesis, we develop two approaches for reasoning about the interactions between the goals of an individual agent. The first of these employs Petri nets to represent and reason about the goals, while the second uses constraint satisfaction techniques to find efficient ways of achieving the goals. Three types of reasoning are incorporated into these models: reasoning about consumable resources where the availability of the resources is limited; the constructive interaction of goals whereby a single plan can be used to achieve multiple goals; and the interleaving of steps for achieving different goals that could cause one or more goals to fail. Experimental evaluation of the two approaches under various different circumstances highlights the benefits of the reasoning developed here whilst also identifying areas where one approach provides better results than the other. This can then be applied to suggest the underlying technique used to implement the reasoning that the agent may want to employ based on the goals it has been assigned