Towards adaptive multi-robot systems: self-organization and self-adaptation

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible

MISSION-ORIENTED HETEROGENEOUS ROBOT COOPERATION BASED ON SMART RESOURCES EXECUTION

Home environments are changing as more technological devices are used to improve daily life. The growing demand for high technology in our homes means that robot integration will soon arrive. Home devices are evolving in a connected paradigm in which data flows to perform efficient home task management. Heterogeneous home robots connected in a network can establish a workflow that complements their capabilities and so increases performance within a mission execution. This work addresses the definition and requirements of a robot-group mission in the home context. The proposed solution relies on a network of smart resources, which are defined as cyber-physical systems that provide high-level service execution. Firstly, control middleware architecture is introduced as the execution base for the Smart resources. Next, the Smart resource topology and its integration within a robotic platform are addressed. Services supplied by Smart resources manage their execution through a robot behavior architecture. Robot behavior execution is hierarchically organized through a mission definition that can be established as an individual or collective approach. Environment model and interaction tasks characterize the operation capabilities of each robot within a mission. Mission goal achievement in a heterogeneous group is enhanced through the complement of the interaction capabilities of each robot. To offer a clearer explanation, a full use case is presented in which two robots cooperate to execute a mission and the previously detailed steps are evaluated. Finally, some of the obtained results are discussed as conclusions and future works is introduced.Los entornos domésticos se encuentran sometidos a un proceso de cambio gracias al empleo de dispositivos tecnológicos que mejoran la calidad de vida de las personas. La creciente demanda de alta tecnología en los hogares señala una próxima incorporación de la robótica de servicio. Los dispositivos domésticos están evolucionando hacia un paradigma de conexión en el cual la información fluye para ofrecer una gestión más eficiente. En este entorno, robots heterogéneos conectados a la red pueden establecer un flujo de trabajo que ofreciendo nuevas soluciones y incrementando la eficiencia en la ejecución de tareas. Este trabajo aborda la definición y los requisitos necesarios para la ejecución de misiones en grupos de robots heterogéneos en entornos domésticos. La solución propuesta se apoya en una red de Smart resources, que son definidos como sistemas ciber-físicos que proporcionan servicios de alto nivel. En primer lugar, se presenta la arquitectura del middleware de control en la cual se basa la ejecución de los Smart resources. A continuación se detalla la topología de los Smart resources, así como su integración en plataformas robóticas. Los servicios proporcionados por los Smart resources gestionan su ejecución mediante una arquitectura de comportamientos para robots. La ejecución de estos comportamientos se organiza de forma jerárquica mediante la definición de una misión con un objetivo establecido de forma individual o colectiva a un grupo de robots. Dentro de una misión, las tareas de modelado e interacción con el entorno define las capacidades de operación de los robots dentro de una misión. Mediante la integración de un grupo heterogéneo de robots sus diversas capacidades son complementadas para el logro un objetivo común. A fin de caracterizar esta propuesta, los mecanismos presentados en este documento se evaluarán en detalle a lo largo de una serie experimentos en los cuales un grupo de robots heterogéneos ejecutan una misión colaborativa para alcanzar un objetivo común. Finalmente, los resultados serán discutidos a modo de conclusiones dando lugar el establecimiento de un trabajo futuro.Els entorns domèstics es troben sotmesos a un procés de canvi gràcies a l'ocupació de dispositius tecnològics que milloren la qualitat de vida de les persones. La creixent demanda d'alta tecnologia a les llars assenyala una propera incorporació de la robòtica de servei. Els dispositius domèstics estan evolucionant cap a un paradigma de connexió en el qual la informació flueix per oferir una gestió més eficient. En aquest entorn, robots heterogenis connectats a la xarxa poden establir un flux de treball que ofereix noves solucions i incrementant l'eficiència en l'execució de tasques. Aquest treball aborda la definició i els requisits necessaris per a l'execució de missions en grups de robots heterogenis en entorns domèstics. La solució proposada es recolza en una xarxa de Smart resources, que són definits com a sistemes ciber-físics que proporcionen serveis d'alt nivell. En primer lloc, es presenta l'arquitectura del middleware de control en la qual es basa l'execució dels Smart resources. A continuació es detalla la tipologia dels Smart resources, així com la seva integració en plataformes robòtiques. Els serveis proporcionats pels Smart resources gestionen la seva execució mitjançant una arquitectura de comportaments per a robots. L'execució d'aquests comportaments s'organitza de forma jeràrquica mitjançant la definició d'una missió amb un objectiu establert de forma individual o col·lectiva a un grup de robots. Dins d'una missió, les tasques de modelatge i interacció amb l'entorn defineix les capacitats d'operació dels robots dins d'una missió. Mitjançant la integració d'un grup heterogeni de robots seves diverses capacitats són complementades per a l'assoliment un objectiu comú. Per tal de caracteritzar aquesta proposta, els mecanismes presentats en aquest document s'avaluaran en detall mitjançant d'una sèrie experiments en els quals un grup de robots heterogenis executen una missió col·laborativa per aconseguir un objectiu comú. Finalment, els resultats seran discutits a manera de conclusions donant lloc a l'establiment d'un treball futur.Munera Sánchez, E. (2017). MISSION-ORIENTED HETEROGENEOUS ROBOT COOPERATION BASED ON SMART RESOURCES EXECUTION [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/88404TESI

AGNI: an API for the control of automomous service robots

With the continuum growth of Internet connected devices, the scalability of the protocols used for communication between them is facing a new set of challenges. In robotics these communications protocols are an essential element, and must be able to accomplish with the desired communication. In a context of a multi-­‐‑agent platform, the main types of Internet communication protocols used in robotics, mission planning and task allocation problems will be revised. It will be defined how to represent a message and how to cope with their transport between devices in a distributed environment, reviewing all the layers of the messaging process. A review of the ROS platform is also presented with the intent of integrating the already existing communication protocols with the ServRobot, a mobile autonomous robot, and the DVA, a distributed autonomous surveillance system. This is done with the objective of assigning missions to ServRobot in a security context

Reconfigurable middleware architectures for large scale sensor networks

Wireless sensor networks, in an effort to be energy efficient, typically lack the high-level abstractions of advanced programming languages. Though strong, the dichotomy between these two paradigms can be overcome. The SENSIX software framework, described in this dissertation, uniquely integrates constraint-dominated wireless sensor networks with the flexibility of object-oriented programming models, without violating the principles of either. Though these two computing paradigms are contradictory in many ways, SENSIX bridges them to yield a dynamic middleware abstraction unifying low-level resource-aware task reconfiguration and high-level object recomposition. Through the layered approach of SENSIX, the software developer creates a domain-specific sensing architecture by defining a customized task specification and utilizing object inheritance. In addition, SENSIX performs better at large scales (on the order of 1000 nodes or more) than other sensor network middleware which do not include such unified facilities for vertical integration

Overlay virtualized wireless sensor networks for application in industrial internet of things : a review

Abstract: In recent times, Wireless Sensor Networks (WSNs) are broadly applied in the Industrial Internet of Things (IIoT) in order to enhance the productivity and efficiency of existing and prospective manufacturing industries. In particular, an area of interest that concerns the use of WSNs in IIoT is the concept of sensor network virtualization and overlay networks. Both network virtualization and overlay networks are considered contemporary because they provide the capacity to create services and applications at the edge of existing virtual networks without changing the underlying infrastructure. This capability makes both network virtualization and overlay network services highly beneficial, particularly for the dynamic needs of IIoT based applications such as in smart industry applications, smart city, and smart home applications. Consequently, the study of both WSN virtualization and overlay networks has become highly patronized in the literature, leading to the growth and maturity of the research area. In line with this growth, this paper provides a review of the development made thus far concerning virtualized sensor networks, with emphasis on the application of overlay networks in IIoT. Principally, the process of virtualization in WSN is discussed along with its importance in IIoT applications. Different challenges in WSN are also presented along with possible solutions given by the use of virtualized WSNs. Further details are also presented concerning the use of overlay networks as the next step to supporting virtualization in shared sensor networks. Our discussion closes with an exposition of the existing challenges in the use of virtualized WSN for IIoT applications. In general, because overlay networks will be contributory to the future development and advancement of smart industrial and smart city applications, this review may be considered by researchers as a reference point for those particularly interested in the study of this growing field

Wireless Sensor Network Virtualization: A Survey

Wireless Sensor Networks (WSNs) are the key components of the emerging Internet-of-Things (IoT) paradigm. They are now ubiquitous and used in a plurality of application domains. WSNs are still domain specific and usually deployed to support a specific application. However, as WSN nodes are becoming more and more powerful, it is getting more and more pertinent to research how multiple applications could share a very same WSN infrastructure. Virtualization is a technology that can potentially enable this sharing. This paper is a survey on WSN virtualization. It provides a comprehensive review of the state-of-the-art and an in-depth discussion of the research issues. We introduce the basics of WSN virtualization and motivate its pertinence with carefully selected scenarios. Existing works are presented in detail and critically evaluated using a set of requirements derived from the scenarios. The pertinent research projects are also reviewed. Several research issues are also discussed with hints on how they could be tackled.Comment: Accepted for publication on 3rd March 2015 in forthcoming issue of IEEE Communication Surveys and Tutorials. This version has NOT been proof-read and may have some some inconsistencies. Please refer to final version published in IEEE Xplor

Aggregate Farming in the Cloud: The AFarCloud ECSEL project

Farming is facing many economic challenges in terms of productivity and cost-effectiveness. Labor shortage partly due to depopulation of rural areas, especially in Europe, is another challenge. Domain specific problems such as accurate monitoring of soil and crop properties and animal health are key factors for minimizing economical risks, and not risking human health. The ECSEL AFarCloud (Aggregate Farming in the Cloud) project will provide a distributed platform for autonomous farming that will allow the integration and cooperation of agriculture Cyber Physical Systems in real-time in order to increase efficiency, productivity, animal health, food quality and reduce farm labor costs. Moreover, such a platform can be integrated with farm management software to support monitoring and decision-making solutions based on big data and real-time data mining techniques.publishedVersio

The role of communication systems in smart grids: Architectures, technical solutions and research challenges

The purpose of this survey is to present a critical overview of smart grid concepts, with a special focus on the role that communication, networking and middleware technologies will have in the transformation of existing electric power systems into smart grids. First of all we elaborate on the key technological, economical and societal drivers for the development of smart grids. By adopting a data-centric perspective we present a conceptual model of communication systems for smart grids, and we identify functional components, technologies, network topologies and communication services that are needed to support smart grid communications. Then, we introduce the fundamental research challenges in this field including communication reliability and timeliness, QoS support, data management services, and autonomic behaviors. Finally, we discuss the main solutions proposed in the literature for each of them, and we identify possible future research directions