Exploiting multi-agent system technology within an autonomous regional active network management system

This paper describes the proposed application of multi-agent system (MAS) technology within AuRA-NMS, an autonomous regional network management system currently being developed in the UK through a partnership between several UK universities, distribution network operators (DNO) and a major equipment manufacturer. The paper begins by describing the challenges facing utilities and why those challenges have led the utilities, a major manufacturer and the UK government to invest in the development of a flexible and extensible active network management system. The requirements the utilities have for a network automation system they wish to deploy on their distribution networks are discussed in detail. With those requirements in mind the rationale behind the use of multi-agent systems (MAS) within AuRA-NMS is presented and the inherent research and design challenges highlighted including: the issues associated with robustness of distributed MAS platforms; the arbitration of different control functions; and the relationship between the ontological requirements of Foundation for Intelligent Physical Agent (FIPA) compliant multi-agent systems, legacy protocols and standards such as IEC 61850 and the common information model (CIM)

A test facility for assessing the performance of IEC61850 substation automation designs

Substation Automation Systems have undergone dramatic changes since the introduction of powerful micro-processing and digital communications devices over Ethernet based networks within the substation. Smart, multifunctional relays, known as Intelligent Electronic Devices, or IEDs, have replaced the traditional panels which contained multiple protection relays, control equipment, metering and status indicators. ActewAGL Distribution, a power utility company servicing Canberra, Australia, has recently decided to undertake a review of its substation automation systems throughout its electrical network. As a result, ActewAGL Distribution has decided to investigate the IEC 61850 – Communication Networks and Systems in Substations standard, by constructing a test facility to assess its performance and capability with the view of implementing the standard into its 132/11kV zone substations network in the near future. This report details the literature review, design, construction, and performance evaluation that was undertaken on the IEC 61850 substation automation designs developed with the use of the test facility. The major achievement of this research project has been the successful development and evaluation of a substation automation system that utilised the IEC 61850 standard incorporated with multiple vendor devices

RFID together with multi-agent systems to control global value chains

Nowadays, the cooperative intelligent transport systems are part of a largest system. Transportations are modal operations integrated in logistics and, logistics is the main process of the supply chain management. The supply chain strategic management as a simultaneous local and global value chain is a collaborative/cooperative organization of stakeholders, many times in co-opetition, to perform a service to the customers respecting the time, place, price and quality levels. The transportation, like other logistics operations must add value, which is achieved in this case through compression lead times and order fulfillments. The complex supplier's network and the distribution channels must be efficient and the integral visibility (monitoring and tracing) of supply chain is a significant source of competitive advantage. Nowadays, the competition is not discussed between companies but among supply chains. This paper aims to evidence the current and emerging manufacturing and logistics system challenges as a new field of opportunities for the automation and control systems research community. Furthermore, the paper forecasts the use of radio frequency identification (RFID) technologies integrated into an information and communication technologies (ICT) framework based on distributed artificial intelligence (DAI) supported by a multi-agent system (MAS), as the most value advantage of supply chain management (SCM) in a cooperative intelligent logistics systems. Logistical platforms (production or distribution) as nodes of added value of supplying and distribution networks are proposed as critical points of the visibility of the inventory, where these technological needs are more evident

A Hierarchical Hybrid Architecture for Mission-Oriented Robot Control

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-03413-3_26In this work is presented a general architecture for a multi physical agent network system based on the coordination and the behaviour management. The system is organised in a hierarchical structure where are distinguished the individual agent actions and the collective ones linked to the whole agent network. Individual actions are also organised in a hybrid layered system that take advantages from reactive and deliberative control. Sensing system is involved as well in the behaviour architecture improving the information acquisition performance.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness under the CICYT project Mission Based Control (COBAMI): DPI2011-28507-C02-02, under coordinated project High Integrity Partitioned Embedded Systems (Hi-PartES): TIN2011-28567-C03-03, and under the collaborative research project supported by the European Union MultiPARTES Project: FP7-ICT 287702. 2011-14.Muñoz Alcobendas, M.; Munera Sánchez, E.; Blanes Noguera, F.; Simó Ten, JE. (2013). A Hierarchical Hybrid Architecture for Mission-Oriented Robot Control. En ROBOT2013: First Iberian Robotics Conference: Advances in Robotics, Vol. 1. Springer. 363-380. https://doi.org/10.1007/978-3-319-03413-3_26S363380Aragues, R.: Consistent data association in multi-robot systems with limited communications. Robotics: Science and Systems, 97–104 (2010)Aragues, R., Cortes, J., Sagues, C.: Distributed consensus on robot networks for dynamically merging feature-based maps. IEEE Transactions on Robotics (2012)Arkin, R.C.: Motor schema based mobile robot navigation. The International Journal of Robotics Research 8(4), 92–112 (1989)Asama, H., Habib, M.K., Endo, I., Ozaki, K., Matsumoto, A., Ishida, Y.: Functional distribution among multiple mobile robots in an autonomous and decentralized robot system. In: Proceedings of the 1991 IEEE International Conference on Robotics and Automation. IEEE (1991)Benet, G., Blanes, F., Martínez, M., Simó, J.: A multisensor robot distributed architecture. In: IFAC Conference INCOM 1998 (1998)Brooks, R.: A robust layered control system for a mobile robot. IEEE Journal of Robotics and Automation 2(1), 14–23 (1986)Canas, J.M., Matellán, V.: Dynamic schema hierarchies for an autonomous robot. In: Garijo, F.J., Riquelme, J.-C., Toro, M. (eds.) IBERAMIA 2002. LNCS (LNAI), vol. 2527, pp. 903–912. Springer, Heidelberg (2002)Choset, H., Nagatani, K.: Topological simultaneous localization and mapping (SLAM): toward exact localization without explicit localization. IEEE Transactions on Robotics and Automation 17(2), 125–137 (2001)Fox, D., Burgard, W., Dellaert, F., Thrun, S.: Monte carlo localization: Efficient position estimation for mobile robots. American Association for Artificial Intelligence, 343–349 (1999)Hu, J., Xie, L., Xu, J.: Vision-based multi-agent cooperative target search. In: Control Automation Robotics & Vision (ICARCV), pp. 895–900 (2012)Huq, R., Mann, G.K.I., Gosine, R.G.: Behavior-modulation technique in mobile robotics using fuzzy discrete event system. IEEE Transactions on Robotics 22(5), 903–916 (2006)Jayasiri, A., Mann, G., Gosine, R.G.: Mobile robot behavior coordination using supervisory control of fuzzy discrete event systems. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2009, pp. 690–695 (2009)Jayasiri, A., Mann, G.K.I., Gosine, R.G.: Behavior coordination of mobile robotics using supervisory control of fuzzy discrete event systems. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 41(5), 1224–1238 (2011)Koenig, N., Howard, A.: Gazebo-3d multiple robot simulator with dynamics. Technical report (2006)Lin, F., Ying, H.: Modeling and control of fuzzy discrete event systems. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 32(4), 408–415 (2002)Madden, J.D.: Multi-robot system based on model of wolf hunting behavior to emulate wolf and elk interactions. In: 2010 IEEE International Conference on Robotics and Biomimetics, ROBIO, pp. 1043–1050 (2010)Mataric, M.J.: Interaction and intelligent behavior. Technical report, DTIC Document (1994)Olivera, V.M., Molina, J.M., Sommaruga, L., et al.: Fuzzy cooperation of autonomous robots. In: Fourth International System on Intelligent Robotics Systems, Lisboa, Portugal (1996)McGann, C., Py, F., Rajan, K., Thomas, H., Henthorn, R., McEwen, R.: A deliberative architecture for auv control. In: IEEE International Conference on Robotics and Automation, ICRA 2008, pp. 1049–1054. IEEE (2008)Munera, E., Muñoz, M., Simó, J., Blanes, F.: Humanoid Robot Self-Location In SPL League. In: Comité Español de Automática (CEA), XXXIII Jornadas de Automatica, 797–804 (2012)Proetzsch, M., Luksch, T., Berns, K.: Development of complex robotic systems using the behavior-based control architecture iB2C. Robotics and Autonomous Systems 58(1), 46–67 (2010)Qiu, D.: Supervisory control of fuzzy discrete event systems: a formal approach. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 35(1), 72–88 (2005)Aladebaran Robotics. NAO Software Documentation 1.12. Technical report (2012)St-Pierre, M., Gingras, D.: Comparison between the unscented Kalman filter and the extended Kalman filter for the position estimation module of an integrated navigation information system. In: 2004 IEEE Intelligent Vehicles Symposium, pp. 831–835 (2004)Stoytchev, A., Arkin, R.C.: Combining deliberation, reactivity, and motivation in the context of a behavior-based robot architecture. In: Proceedings of the 2001 IEEE International Symposium on Computational Intelligence in Robotics and Automation, pp. 290–295 (2001)Nicolau, V., Muñoz, M., Simó, J.: KertrolBot Platform. SiDiReLi: Distributed System with Limited Resources. Technical report, Institute of Control Systems and Industrial Computing - Polytechnic University of Valencia, Valencia, Spain (2011

The Responsibility Quantification (ResQu) Model of Human Interaction with Automation

Intelligent systems and advanced automation are involved in information collection and evaluation, in decision-making and in the implementation of chosen actions. In such systems, human responsibility becomes equivocal. Understanding human casual responsibility is particularly important when intelligent autonomous systems can harm people, as with autonomous vehicles or, most notably, with autonomous weapon systems (AWS). Using Information Theory, we develop a responsibility quantification (ResQu) model of human involvement in intelligent automated systems and demonstrate its applications on decisions regarding AWS. The analysis reveals that human comparative responsibility to outcomes is often low, even when major functions are allocated to the human. Thus, broadly stated policies of keeping humans in the loop and having meaningful human control are misleading and cannot truly direct decisions on how to involve humans in intelligent systems and advanced automation. The current model is an initial step in the complex goal to create a comprehensive responsibility model, that will enable quantification of human causal responsibility. It assumes stationarity, full knowledge regarding the characteristic of the human and automation and ignores temporal aspects. Despite these limitations, it can aid in the analysis of systems designs alternatives and policy decisions regarding human responsibility in intelligent systems and advanced automation

Intelligent monitoring of the health and performance of distribution automation

With a move to 'smarter' distribution networks through an increase in distribution automation and active network management, the volume of monitoring data available to engineers also increases. It can be onerous to interpret such data to produce meaningful information about the health and performance of automation and control equipment. Moreover, indicators of incipient failure may have to be tracked over several hours or days. This paper discusses some of the data analysis challenges inherent in assessing the health and performance of distribution automation based on available monitoring data. A rule-based expert system approach is proposed to provide decision support for engineers regarding the condition of these components. Implementation of such a system using a complex event processing system shell, to remove the manual task of tracking alarms over a number of days, is discussed

Theoretical, Measured and Subjective Responsibility in Aided Decision Making

When humans interact with intelligent systems, their causal responsibility for outcomes becomes equivocal. We analyze the descriptive abilities of a newly developed responsibility quantification model (ResQu) to predict actual human responsibility and perceptions of responsibility in the interaction with intelligent systems. In two laboratory experiments, participants performed a classification task. They were aided by classification systems with different capabilities. We compared the predicted theoretical responsibility values to the actual measured responsibility participants took on and to their subjective rankings of responsibility. The model predictions were strongly correlated with both measured and subjective responsibility. A bias existed only when participants with poor classification capabilities relied less-than-optimally on a system that had superior classification capabilities and assumed higher-than-optimal responsibility. The study implies that when humans interact with advanced intelligent systems, with capabilities that greatly exceed their own, their comparative causal responsibility will be small, even if formally the human is assigned major roles. Simply putting a human into the loop does not assure that the human will meaningfully contribute to the outcomes. The results demonstrate the descriptive value of the ResQu model to predict behavior and perceptions of responsibility by considering the characteristics of the human, the intelligent system, the environment and some systematic behavioral biases. The ResQu model is a new quantitative method that can be used in system design and can guide policy and legal decisions regarding human responsibility in events involving intelligent systems