Coloured Petri nets and graphical simulation for the validation of a robotic cell in aircraft industry

This paper proposes a mixed validation approach based on coloured Petri nets and 3D graphic simulation for the design of supervisory systems in manufacturing cells with multiple robots. The coloured Petri net is used to model the cell behaviour at a high level of abstraction. It models the activities of each cell component and its coordination by a supervisory system. The graphical simulation is used to analyse and validate the cell behaviour in a 3D environment, allowing the detection of collisions and the calculation of process times. The motivation for this work comes from the aeronautic industry. The automation of a fuselage assembly process requires the integration of robots with other cell components such as metrological or vision systems. In this cell, the robot trajectories are defined by the supervisory system and results from the coordination of the cell components. The paper presents the application of the approach for an aircraft assembly cell under integration in Brazil. This case study shows the feasibility of the approach and supports the discussion of its main advantages and limits. (C) 2011 Elsevier Ltd. All rights reserved.

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

Desenvolvimento e Controlo de um Veículo Autónomo Aéreo Quadrotor

A crescente necessidade de meios de inspecção e recolha de informação de infraestruturas e do meio ambiente natural, origina o recurso a meios tecnológicos cada vez mais evoluídos. Neste contexto, os robôs móveis autónomos aéreos surgem como uma ferramenta importante. Em particular, os veículos aéreos de asa móvel, pela sua manobrabilidade e controlo podem-se utilizar eficazmente em meios complexos como cenários interiores onde o ambiente é parcialmente controlado. A sua utilização em coordenação com outros veículos robóticos móveis e em particular com a crescente autonomia de decisão, permitem uma eficiência elevada, por exemplo, em tarefas de recolha automática de informação, vigilância, apoio a comunicações, etc. A inexistência de um veículo autónomo de asa móvel no cenário multi-robótico desenvolvido pelo Laboratório de Sistemas Autónomos do Instituto Superior de Engenharia do Porto, aliada às suas aplicações referidas, criou a necessidade do desenvolvimento de um veículo desta gama. Identificou-se, pois, o desenvolvimento de um veículo autónomo aéreo do tipo quadrotor com capacidade de vôo base estabilizado como o problema a resolver. Foi efectuado um levantamento de requisitos do sistema, a caracterização de um veículo autónomo aéreo Vertical Take-off and Landing - VTOL, e efectuado um trabalho de pesquisa a fim de possibilitar o conhecimento das técnicas e tecnologias envolvidas. Tendo em vista o objectivo de controlo e estabilização do veículo, foi efectuada a modelização do sistema que serviu não só para a melhor compreensão da sua dinâmica mas também para o desenvolvimento de um simulador que possibilitou a validação de estratégias de controlo e avaliação de comportamentos do veículo para diferentes cenários. A inexistência de controladores de motores brushless adequada (frequência de controlo), originou o desenvolvimento de um controlador dedicado para motores brushless, motores esses utilizados para a propulsão do veículo. Este controlador permite uma taxa de controlo a uma frequência de 20KHz, possui múltiplas interfaces de comunicação (CAN, RS232, Ethernet, SPI e JTAG), é de reduzido peso e dimensões e modular, visto ter sido implementado em dois módulos, i.e., permite a sua utilização com diferentes interfaces de potência. Projectou-se um veículo autónomo aéreo em termos físicos com a definição da sua arquitectura de hardware e software bem como o sistema de controlo de vôo. O sistema de estabilização de vôo compreende o processamento de informação fornecida por um sistema de navegação inercial, um sonar e o envio de referências de velocidade para cada um dos nós de controlo ligados a um barramento CAN instalado no veículo. A implementação do veículo foi alcançada nas suas vertentes mecânica, de hardware e software. O UAV foi equipado com um sistema computacional dotando-o de capacidades para o desempenho de tarefas previamente analisadas. No presente trabalho, são também tiradas algumas conclusões sobre o desenvolvimento do sistema e sua implementação bem como perspectivada a sua evolução futura no contexto de missões coordenadas de múltiplos veículos robóticos.

Design and Control of an Anthropomorphic Robotic Finger with Multi-point Tactile Sensation

The goal of this research is to develop the prototype of a tactile sensing platform for anthropomorphic manipulation research. We investigate this problem through the fabrication and simple control of a planar 2-DOF robotic finger inspired by anatomic consistency, self-containment, and adaptability. The robot is equipped with a tactile sensor array based on optical transducer technology whereby localized changes in light intensity within an illuminated foam substrate correspond to the distribution and magnitude of forces applied to the sensor surface plane. The integration of tactile perception is a key component in realizing robotic systems which organically interact with the world. Such natural behavior is characterized by compliant performance that can initiate internal, and respond to external, force application in a dynamic environment. However, most of the current manipulators that support some form of haptic feedback either solely derive proprioceptive sensation or only limit tactile sensors to the mechanical fingertips. These constraints are due to the technological challenges involved in high resolution, multi-point tactile perception. In this work, however, we take the opposite approach, emphasizing the role of full-finger tactile feedback in the refinement of manual capabilities. To this end, we propose and implement a control framework for sensorimotor coordination analogous to infant-level grasping and fixturing reflexes. This thesis details the mechanisms used to achieve these sensory, actuation, and control objectives, along with the design philosophies and biological influences behind them. The results of behavioral experiments with a simple tactilely-modulated control scheme are also described. The hope is to integrate the modular finger into an %engineered analog of the human hand with a complete haptic system.

Investigating feasible tools for swarm pattern transformation

Abstract-The work reported in this paper is motivated by the need for developing swarm pattern transformation methodologies. Two methods, namely a macroscopic method and a mathematical method are investigated for pattern transformation. The first method is based on macroscopic parameters while the second method is based on both microscopic and macroscopic parameters. A formal definition to pattern transformation considering four special cases of transformation is presented. Simulations on a physics simulation engine are used to confirm the feasibility of the proposed transformation methods. A brief comparison between the two methods is also presented.

Aprendizado por Reforço com Valores deInfluência em Sistemas Multi-Agente

We propose a new paradigm for collective learning in multi-agent systems (MAS) as a solution to the problem in which several agents acting over the same environment must learn how to perform tasks, simultaneously, based on feedbacks given by each one of the other agents. We introduce the proposed paradigm in the form of a reinforcement learning algorithm, nominating it as reinforcement learning with influence values. While learning by rewards, each agent evaluates the relation between the current state and/or action executed at this state (actual believe) together with the reward obtained after all agents that are interacting perform their actions. The reward is a result of the interference of others. The agent considers the opinions of all its colleagues in order to attempt to change the values of its states and/or actions. The idea is that the system, as a whole, must reach an equilibrium, where all agents get satisfied with the obtained results. This means that the values of the state/actions pairs match the reward obtained by each agent. This dynamical way of setting the values for states and/or actions makes this new reinforcement learning paradigm the first to include, naturally, the fact that the presence of other agents in the environment turns it a dynamical model. As a direct result, we implicitly include the internal state, the actions and the rewards obtained by all the other agents in the internal state of each agent. This makes our proposal the first complete solution to the conceptual problem that rises when applying reinforcement learning in multi-agent systems, which is caused by the difference existent between the environment and agent models. With basis on the proposed model, we create the IVQ-learning algorithm that is exhaustive tested in repetitive games with two, three and four agents and in stochastic games that need cooperation and in games that need collaboration. This algorithm shows to be a good option for obtaining solutions that guarantee convergence to the Nash optimum equilibrium in cooperative problems. Experiments performed clear shows that the proposed paradigm is theoretical and experimentally superior to the traditional approaches. Yet, with the creation of this new paradigm the set of reinforcement learning applications in MAS grows up. That is, besides the possibility of applying the algorithm in traditional learning problems in MAS, as for example coordination of tasks in multi-robot systems, it is possible to apply reinforcement learning in problems that are essentially collaborative

Estratégias baseadas em aprendizado para coordenação de uma frota de robôs em tarefas cooperativas

In multi-robot systems, both control architecture and work strategy represent a challenge for researchers. It is important to have a robust architecture that can be easily adapted to requirement changes. It is also important that work strategy allows robots to complete tasks efficiently, considering that robots interact directly in environments with humans. In this context, this work explores two approaches for robot soccer team coordination for cooperative tasks development. Both approaches are based on a combination of imitation learning and reinforcement learning. Thus, in the first approach was developed a control architecture, a fuzzy inference engine for recognizing situations in robot soccer games, a software for narration of robot soccer games based on the inference engine and the implementation of learning by imitation from observation and analysis of others robotic teams. Moreover, state abstraction was efficiently implemented in reinforcement learning applied to the robot soccer standard problem. Finally, reinforcement learning was implemented in a form where actions are explored only in some states (for example, states where an specialist robot system used them) differently to the traditional form, where actions have to be tested in all states. In the second approach reinforcement learning was implemented with function approximation, for which an algorithm called RBF-Sarsa($lambda$) was created. In both approaches batch reinforcement learning algorithms were implemented and imitation learning was used as a seed for reinforcement learning. Moreover, learning from robotic teams controlled by humans was explored. The proposal in this work had revealed efficient in the robot soccer standard problem and, when implemented in other robotics systems, they will allow that these robotics systems can efficiently and effectively develop assigned tasks. These approaches will give high adaptation capabilities to requirements and environment changes.

Cooperative Task Execution between Modular Robots Based on Tight-Loose Cooperation Strategies

The complexity in the execution of cooperative tasks is high due to the fact that a robot team requires movement coordination at the beginning of the mission and continuous coordination during the execution of the task. A variety of techniques have been proposed to give a solution to this problem assuming standard mobile robots. This work focuses on presenting the execution of a cooperative task by a modular robot team. The complexity of the task execution increases due to the fact that each robot is composed of modules which have to be coordinated in a proper way to successfully work. A combined tight and loose cooperation strategy is presented and a bar-pushing example is used as a cooperative task to show the performance of this type of system.

The morphofunctional approach to emotion modelling in robotics

In this conceptual paper, we discuss two areas of research in robotics, robotic models of emotion and morphofunctional machines, and we explore the scope for potential cross-fertilization between them. We shift the focus in robot models of emotion from information-theoretic aspects of appraisal to the interactive significance of bodily dispositions. Typical emotional phenomena such as arousal and action readiness can be interpreted as morphofunctional processes, and their functionality may be replicated in robotic systems with morphologies that can be modulated for real-time adaptation. We investigate the control requirements for such systems, and present a possible bio-inspired architecture, based on the division of control between neural and endocrine systems in humans and animals. We suggest that emotional epi- sodes can be understood as emergent from the coordination of action control and action-readiness, respectively. This stress on morphology complements existing research on the information-theoretic aspects of emotion.

Control por modos deslizantes como estrategia de navegación en una flota de robots

En esta tesis se presenta el desarrollo de un esquema de cooperación entre vehículos terrestres (UGV) y aéreos (UAV) no tripulados, que sirve de base para conformar dos flotas de robots autónomos (denominadas FRACTAL y RoMA). Con el fin de comprobar, en diferentes escenarios y con diferente tareas, la validez de las estrategias de coordinación y cooperación propuestas en la tesis se utilizan los robots de la flota FRACTAL, que sirven como plataforma de prueba para tareas como el uso de vehículos aéreos y terrestres para apoyar labores de búsqueda y rescate en zonas de emergencia y la cooperación de una flota de robots para labores agrícolas. Se demuestra además, que el uso de la técnica de control no lineal conocida como Control por Modos Deslizantes puede ser aplicada no solo para conseguir la navegación autónoma individual de un robot aéreo o terrestre, sino también en tareas que requieren la navegación coordinada y sin colisiones de varios robots en un ambiente compartido. Para esto, se conceptualiza teóricamente el uso de la técnica de Control por Modos Deslizantes como estrategia de coordinación entre robots, extendiendo su aplicación a robots no-holonómicos en R2 y a robots aéreos en el espacio tridimensional. Después de dicha contextualización teórica, se analizan las condiciones necesarias para determinar la estabilidad del sistema multi-robot controlado y, finalmente, se comprueban las características de estabilidad y robustez ofrecidas por esta técnica de control. Tales comprobaciones se hacen simulando la navegación segura y eficiente de un grupo de UGVs para la detección de posibles riesgos ambientales, aprovechando la información aportada por un UAV. Para estas simulaciones se utilizan los modelos matemáticos de robots de la flota RoMA. Estas tareas coordinadas entre los robots se hacen posibles gracias a la efectividad, estabilidad y robustez de las estrategias de control que se desarrollan como núcleo fundamental de este trabajo de investigación. ABSTRACT This thesis presents the development of a cooperation scheme between unmanned ground (UGV) and aerial (UAV) vehicles. This scheme is the basis for forming two fleets of autonomous robots (called FRACTAL and RoMA). In order to assess, in different settings and on different tasks, the validity of the coordination and cooperation strategies proposed in the thesis, the FRACTAL fleet robots serves as a test bed for tasks like using coordinated aerial and ground vehicles to support search and rescue work in emergency scenarios or cooperation of a fleet of robots for agriculture. It is also shown that using the technique of nonlinear control known as Sliding Modes Control (SMC) can be applied not only for individual autonomous navigation of an aircraft or land robot, but also in tasks requiring the coordinated navigation of several robots, without collisions, in a shared environment. To this purpose, a strategy of coordination between robots using Sliding Mode Control technique is theoretically conceptualized, extending its application to non-holonomic robots in R2 and aerial robots in three-dimensional space. After this theoretical contextualization, the stability conditions of multi-robot system are analyzed, and finally, the stability and robustness characteristics are validated. Such validations are made with simulated experiments about the safe and efficient navigation of a group of UGV for the detection of possible environmental hazards, taking advantage of the information provided by a UAV. This simulations are made using mathematical models of RoMA fleet robots. These coordinated tasks of robots fleet are made possible thanks to the effectiveness, stability and robustness of the control strategies developed as core of this research.

Decision Making for Teams of Mobile Robots

In the past years, we could observe a significant amount of new robotic systems in science, industry, and everyday life. To reduce the complexity of these systems, the industry constructs robots that are designated for the execution of a specific task such as vacuum cleaning, autonomous driving, observation, or transportation operations. As a result, such robotic systems need to combine their capabilities to accomplish complex tasks that exceed the abilities of individual robots. However, to achieve emergent cooperative behavior, multi-robot systems require a decision process that copes with the communication challenges of the application domain. This work investigates a distributed multi-robot decision process, which addresses unreliable and transient communication. This process composed by five steps, which we embedded into the ALICA multi-agent coordination language guided by the PROViDE negotiation middleware. The first step encompasses the specification of the decision problem, which is an integral part of the ALICA implementation. In our decision process, we describe multi-robot problems by continuous nonlinear constraint satisfaction problems. The second step addresses the calculation of solution proposals for this problem specification. Here, we propose an efficient solution algorithm that integrates incomplete local search and interval propagation techniques into a satisfiability solver, which forms a satisfiability modulo theories (SMT) solver. In the third decision step, the PROViDE middleware replicates the solution proposals among the robots. This replication process is parameterized with a distribution method, which determines the consistency properties of the proposals. In a fourth step, we investigate the conflict resolution. Therefore, an acceptance method ensures that each robot supports one of the replicated proposals. As we integrated the conflict resolution into the replication process, a sound selection of the distribution and acceptance methods leads to an eventual convergence of the robot proposals. In order to avoid the execution of conflicting proposals, the last step comprises a decision method, which selects a proposal for implementation in case the conflict resolution fails. The evaluation of our work shows that the usage of incomplete solution techniques of the constraint satisfaction solver outperforms the runtime of other state-of-the-art approaches for many typical robotic problems. We further show by experimental setups and practical application in the RoboCup environment that our decision process is suitable for making quick decisions in the presence of packet loss and delay. Moreover, PROViDE requires less memory and bandwidth compared to other state-of-the-art middleware approaches.

Cheaper Faster Drug Development Validated By The Repositioning Of Drugs Against Neglected Tropical Diseases.

There is an urgent need to make drug discovery cheaper and faster. This will enable the development of treatments for diseases currently neglected for economic reasons, such as tropical and orphan diseases, and generally increase the supply of new drugs. Here, we report the Robot Scientist 'Eve' designed to make drug discovery more economical. A Robot Scientist is a laboratory automation system that uses artificial intelligence (AI) techniques to discover scientific knowledge through cycles of experimentation. Eve integrates and automates library-screening, hit-confirmation, and lead generation through cycles of quantitative structure activity relationship learning and testing. Using econometric modelling we demonstrate that the use of AI to select compounds economically outperforms standard drug screening. For further efficiency Eve uses a standardized form of assay to compute Boolean functions of compound properties. These assays can be quickly and cheaply engineered using synthetic biology, enabling more targets to be assayed for a given budget. Eve has repositioned several drugs against specific targets in parasites that cause tropical diseases. One validated discovery is that the anti-cancer compound TNP-470 is a potent inhibitor of dihydrofolate reductase from the malaria-causing parasite Plasmodium vivax.

Different coordination modes for disulfoxides towards diorganotin(IV) dichlorides. X-ray crystal structures of 1,2-cis-bis-(phenylsulfinyl)ethene (rac-,cis-cbpse) and adducts [{Ph2SnCl2(meso-bpse)}n] and [{n-Bu2SnCl2(pdtd)}2]

The reactions of meso-1,2-bis(phenylsulfinyl)ethane (meso-bpse) with Ph2SnCl2, 2-phenyl-1,3-dithiane trans-1-trans-3-dioxide (pdtd) with n-Bu2SnCl2 and 1,2-cis-bis-(phenylsulfinyl)ethene (rac-,cis-cbpse) with Ph2SnCl2, in 1:1 molar ratio, yielded [{Ph2SnCl2(meso-bpse)}n], [{n-Bu2SnCl2(pdtd)}2] and [{Ph2SnCl2(rac,cis-cbpse)}x] (x = 2 or n), respectively. All adducts were studied by IR, Mössbauer and 119Sn NMR spectroscopic methods, elemental analysis and single crystal X-ray diffractometry. The X-ray crystal structure of [{Ph2SnCl2(meso-bpse)}n] revealed the occurrence of infinite chains in which the tin(IV) atoms appear in a distorted octahedral geometry with Cl atoms in cis and Ph groups in trans positions. The X-ray crystal structure of [{n-Bu2SnCl2(pdtd)}2] revealed discrete centrosymmetric dimeric species in which the tin(IV) atoms possess a distorted octahedral geometry with bridging disulfoxides in cis and n-butyl moieties in trans positions. The spectroscopic data indicated that the adduct containing the rac,cis-cbpse ligand can be dimeric or polymeric. The X-ray structural analysis of the free rac-,cis-cbpse sulfoxide revealed that the crystals belong to the C2/c space group.

Metallochlorophylls of magnesium, copper and zinc: evaluation of the influence of the first coordination sphere on their solvatochromism and aggregation properties

In this study the role of different metal centers (magnesium, zinc and copper) on the enhancement of the hydrophilic character of metallochlorophylls, was evaluated. The solvatochromism as well as the aggregation process for these compounds in water/ethanol mixtures at different volume ratios were evaluated using Fluorescence, and Resonant Light Scattering (RLS) measurements, aiming to characterize the behavior of these compounds. Independently on the studied metallochlorophyll, the presence of at least 60% of water results in a considerable increase in the fluorescence emission, probably a direct consequence of a lower aggregation of these compounds, which is confirmed by the results from RLS measurements. Additionally, the results suggest that magnesium and zinc chlorophyll should be promising phototherapeutic agents for Photodynamic Therapy.