Cooperation mechanism for team-work based multi-agent system in dynamic scheduling through meta-heuristics

This paper describes a Multi-agent Scheduling System that assumes the existence of several Machines Agents (which are decision-making entities) distributed inside the Manufacturing System that interact and cooperate with other agents in order to obtain optimal or near-optimal global performances. Agents have to manage their internal behaviors and their relationships with other agents via cooperative negotiation in accordance with business policies defined by the user manager. Some Multi Agent Systems (MAS) organizational aspects are considered. An original Cooperation Mechanism for a Team-work based Architecture is proposed to address dynamic scheduling using Meta-Heuristics.

Coordinated transportation of a large object by a team of three robots

Dynamical systems theory in this work is used as a theoretical language and tool to design a distributed control architecture for a team of three robots that must transport a large object and simultaneously avoid collisions with either static or dynamic obstacles. The robots have no prior knowledge of the environment. The dynamics of behavior is defined over a state space of behavior variables, heading direction and path velocity. Task constraints are modeled as attractors (i.e. asymptotic stable states) of the behavioral dynamics. For each robot, these attractors are combined into a vector field that governs the behavior. By design the parameters are tuned so that the behavioral variables are always very close to the corresponding attractors. Thus the behavior of each robot is controlled by a time series of asymptotical stable states. Computer simulations support the validity of the dynamical model architecture.

Coordinated transportation of a large object by a team of two robots

In this paper dynamical systems theory is used as a theoretical language and tool to design a distributed control architecture for a team of two robots that must transport a large object and simultaneously avoid collisions with obstacles (either static or dynamic). This work extends the previous work with two robots (see [1] and [5]). However here we demonstrate that it’s possible to simplify the architecture presented in [1] and [5] and reach an equally stable global behavior. The robots have no prior knowledge of the environment. The dynamics of behavior is defined over a state space of behavior variables, heading direction and path velocity. Task constrains are modeled as attractors (i.e. asymptotic stable states) of a behavioral dynamics. For each robot, these attractors are combined into a vector field that governs the behavior. By design the parameters are tuned so that the behavioral variables are always very close to the corresponding attractors. Thus the behavior of each robot is controlled by a time series of asymptotic stable states. Computer simulations support the validity of the dynamical model architecture.

Design of the ISePorto robocup Middle-Size League Robotic Soccer Team: Control, Localisation and Coordination

Proceedings of the 10th Mediterranean Conference on Control and Automation - MED2002 Lisbon, Portugal, July 9-12, 2002

Control and Localisation for the ISePorto Robotic Soccer Team

International Conference on Advanced Robotics, Coimbra, Portugal, Julho 2003

ISePorto Robotic Soccer Team: A New Player Generation

Proceedings of the Scientific Meeting of the Portuguese Robotics Open 2004

Integration of the project team in the classic maintenance cycle

A manutenção é uma área extremamente importante, principalmente na indústria. Devidamente organizada, permitirá um fluxo produtivo devidamente planeado e executado, que permitirá a qualquer empresa manter o nível de facturação desejado e o prazo de entrega acordado com os clientes. De outra forma, poderá originar o caos. No entanto, os desafios de gestão da produção mais correntes, nomeadamente através do Lean Manufacturing, passam a exigir um pouco mais do que uma simples manutenção. Torna-se obrigatório fazer análises económicas que permitam averiguar quando cada equipamento passa a exigir custos de manutenção excessivos, os quais poderão obrigar a um recondicionamento mais acentuado do equipamento, o qual pode passar inclusivamente por uma melhoria da sua performance. Nestes casos, terá que existir uma “cumplicidade” entre a Direcção de Produção e a Manutenção, no sentido de averiguar o melhor momento para proceder a uma melhoria do equipamento, numa perspectiva de funcionamento global em linha de produção, adaptando-o à performance que será exigida ao conjunto. Neste domínio, o Projecto passa a prestar um serviço valiosíssimo à empresa, integrando-se no conjunto Produção + Manutenção, criando valor na intervenção, através do desenvolvimento de um trabalho que permite não só repor o estado natural da produção, mas sim promover uma melhoria sustentada da mesma. Este trabalho pretende reflectir e avaliar a relevância do Projecto neste tipo de operações, contribuindo de uma forma sistemática e sustentada para a melhoria contínua dos processos de fabrico. É apresentado um caso de estudo que pretende validar todo o desenvolvimento anteriormente realizado na matéria.