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Development of flexible languages for scenario and team description in multirobot missions

Published online by Cambridge University Press:  02 May 2016

Daniel Castro Silva ,
Pedro Henriques Abreu ,
Luís Paulo Reis  and
Eugénio Oliveira
Daniel Castro Silva*
Affiliation:
Department of Informatics Engineering, Faculty of Engineering, University of Porto, Porto, Portugal Artificial Intelligence and Computer Science Laboratory, Faculty of Engineering, University of Porto, Porto, Portugal
Pedro Henriques Abreu
Affiliation:
Department of Informatics Engineering, University of Coimbra, Coimbra, Portugal Centre for Informatics and Systems, University of Coimbra, Coimbra, Portugal
Luís Paulo Reis
Affiliation:
Artificial Intelligence and Computer Science Laboratory, Faculty of Engineering, University of Porto, Porto, Portugal School of Engineering, University of Minho, Campus de Azurém, Guimarães, Portugal
Eugénio Oliveira
Affiliation:
Department of Informatics Engineering, Faculty of Engineering, University of Porto, Porto, Portugal Artificial Intelligence and Computer Science Laboratory, Faculty of Engineering, University of Porto, Porto, Portugal
*
Reprint requests to: Daniel Castro Silva, Department of Informatics Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias s/n, 4200-465 Porto, Portugal. E-mail: [email protected]
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Abstract

The work described in this paper is part of the development of a framework to support the joint execution of cooperative missions by a group of vehicles, in a simulated, augmented, or real environment. Such a framework brings forward the need for formal languages in which to specify the vehicles that compose a team, the scenario in which they will operate, and the mission to be performed. This paper introduces the Scenario Description Language (SDL) and the Team Description Language (TDL), two Extensible Markup Language based dialects that compose the static components necessary for representing scenario and mission knowledge. SDL provides a specification of physical scenario and global operational constraints, while TDL defines the team of vehicles, as well as team-specific operational restrictions. The dialects were defined using Extensible Markup Language schemas, with all required information being integrated in the definitions. An interface was developed and incorporated into the framework, allowing for the creation and edition of SDL and TDL files. Once the information is specified, it can be used in the framework, thus facilitating environment and team specification and deployment. A survey answered by practitioners and researchers shows that the satisfaction with SDL+TDL is elevated (the overall evaluation of SDL+TDL achieved a score of 4 out of 5, with 81%/78.6% of the answers ≥4); in addition, the usability of the interface was evaluated, achieving a score of 86.7 in the System Usability Scale survey. These results imply that SDL+TDL is flexible enough to represent scenarios and teams, through a user-friendly interface.

Keywords

Extensible Markup Language DialectKnowledge RepresentationMultivehicle MissionScenario DefinitionTeam Definition
Type
Regular Articles
Information
AI EDAM , Volume 31 , Issue 1 , February 2017 , pp. 69 - 86
Copyright
Copyright © Cambridge University Press 2016 

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References

REFERENCES

Abreu, P.H., Mendes-Moreira, J., Costa, I., Castelão, D., Reis, L.P., & Garganta, J. (2012). Human versus virtual robotics soccer: A technical analysis. European Journal of Sport Science 12(1), 26–36.Google Scholar
Allen, S., Burke, E.K., Hyde, M.R., & Kendall, G. (2009). Evolving reusable 3D packing heuristics with genetic programming. Proc. 11th Annual Genetic and Evolutionary Computation Conf., GECCO 2009 (Rothlauf, F., Ed.), pp. 931–938. New York: ACM.Google Scholar
Almeida, F., Abreu, P.H., Lau, N., & Reis, L.P. (2013). An automatic approach to extract goal plans from soccer simulated matches. Soft Computing 17(5), 835–848.Google Scholar
Aloisio, G., Conte, D., Elefante, C., Epicoco, I., Marra, G.P., Mastrantonio, G., & Quarta, G. (2006). SensorML for grid sensor networks. Proc. 2006 Int. Conf. Grid Computing & Applications, GCA 2006, pp. 147–152, Las Vegas, NV, June 26–29.Google Scholar
ANSI/AIIM. (2009). Standard Recommended Practice—Strategy Markup Language: Part 1. StratML Core. Standard ANSI/AIIM 21. New York: ANSI/AIIM.Google Scholar
Brooke, J. (1996). SUS—A quick and dirty usability scale. In Usability Evaluation in Industry (Jordan, P.W., Thomas, B., McClelland, I.L., & Weerdmeester, B., Eds.), pp. 189–194. London: Taylor & Francis.Google Scholar
Brunk, B.K., & Porosnicu, E. (2004). A tour of the AIXM concepts. 24th Annual ESRI Int. User Conf., San Diego, CA, August 9–13.Google Scholar
Brunk, B.K., & Porosnicu, E. (2005). Aeronautical information exchange model (AIXM) GIS interoperability through GML. Proc. 25th Annual ESRI Int. User Conf., San Diego, CA, July 25–29.Google Scholar
Brunner, H., Mikula, A., & Eier, D. (2007). A concept for service based information quality and safety enhancement in aeronautical information management. Proc. 52nd Annual Conf. Air Traffic Control Association 2007, pp. 43–47, Washington, DC, October 28–31.Google Scholar
Camara, A., Silva, D.C., Abreu, P.H., & Oliveira, E. (2014). Comparing centralized and decentralized multi-agent approaches to air traffic control. Proc. 28th European Simulation and Modelling Conf., ESM'2014, pp. 189–193, Porto, Portugal, October 22–24.Google Scholar
Casbeer, D.W., Kingston, D.B., Beard, R.W., & McLain, T.W. (2006). Cooperative forest fire surveillance using a team of small unmanned air vehicles. International Journal of Systems Science 37(6), 351–360.Google Scholar
Deursen, D.V., Bruyne, S.D., Lancker, W.V., Neve, W.D., Schrijver, D.D., Hellwagner, H., & de Walle, R.V. (2007). Mu-MiVA: a multimedia delivery platform using format-agnostic, XML-driven content adaptation. Proc. 9th IEEE Int. Symp. Multimedia (ISM ’07), pp. 131–138. Los Alamitos, CA: IEEE Computer Society.Google Scholar
Fan, H., Meng, L., & Jahnke, M. (2009). Generalization of 3D buildings modelled by CityGML. Advances in GIScience: Proc. 12th AGILE Conf. (Sester, M., Bernard, L., & Paelke, V., Eds.), Lecture Notes in Geoinformation and Cartography, pp. 387–405. Berlin: Springer.Google Scholar
Federal Aviation Administration. (2010). Temporary flight restrictions. Accessed at http://tfr.faa.gov/tfr2/list.htmlGoogle Scholar
Flight One Software, Inc. (2009). Airport Facilitator X Manual, 1.08 ed. Accessed at http://www.flight1.comGoogle Scholar
Georgieva, A., & Georgiev, B. (2010). Nontraditional approach to XML web services interactions. Proc. 5th Int. Conf. Internet and Web Applications and Services, pp. 67–72. Los Alamitos, CA: IEEE Computer Society.Google Scholar
Gimenes, R., Silva, D.C., Reis, L.P., & Oliveira, E. (2008). Flight simulation environments applied to agent-based autonomous UAVs. Proc. 10th Int. Conf. Enterprise Information Systems (ICEIS 2008), pp. 243–246, Barcelona, June 12–16.Google Scholar
Groppe, S., Groppe, J., Böttcher, S., Wycisk, T., & Gruenwald, L. (2009). Optimizing the execution of XSLT style sheets for querying transformed XML data. Knowledge and Information Systems 18(3), 331–391.Google Scholar
Hobbs, R.L. (2003). Using XML to support military decision-making. Proc. XML Conf. Exposition 2003, XML 2003, Philadelphia, PA, December 7–12.Google Scholar
Huang, C.-H., Chuang, T.-R., Deng, D.-P., & Lee, H.-M. (2009). Building GML-native web-based geographic information systems. Computers & Geosciences 35(9), 1802–1816.Google Scholar
Kumar, C.S., Govardhan, A., & Rao, C.G. (2009). Usage of XML technology in electronic health record for effective heterogeneous systems integration in healthcare. International Journal of Medical Engineering and Informatics 1(4), 399–406.Google Scholar
Lewis, J.R., & Sauro, J. (2009). The factor structure of the system usability scale. Proc. 1st Int. Conf. Human Centered Design, pp. 94–103. San Diego, CA: Springer–Verlag.Google Scholar
Masterson, J., Keeshan, B., & Hauck, H. (2009). Airport design editor use manual, 1.47 ed. ScruffyDuck Software Company. Accessed at http://www.scruffyduck.org/airport-design-editor/4584106799Google Scholar
Microsoft Corporation. (2008). Compiling BGL. Microsoft Developer Network, Microsoft ESP SDK. Accessed at http://msdn.microsoft.com/en-us/library/cc526978.aspxGoogle Scholar
Microsoft Corporation. (2010). XML Schema Definition Tool (Xsd.exe). Microsoft Developer Network Library. Accessed at http://msdn.microsoft.com/en-us/library/x6c1kb0s.aspxGoogle Scholar
Open Geospatial Consortium. (2007 a). OpenGIS Geography Markup Language (GML) Encoding Standard. OpenGIS Standard OGC 07–036, Open Geospatial Consortium Inc. Accessed at http://www.opengeospatial.org/Google Scholar
Open Geospatial Consortium. (2007 b). OpenGIS Sensor Model Language (SensorML) Implementation Specification. OpenGIS Implementation Specification OGC 07–000, Open Geospatial Consortium Inc. Accessed at http://www.opengeospatial.org/Google Scholar
Open Geospatial Consortium. (2008). OpenGIS City Geography Markup Language (CityGML) Encoding Standard. OpenGIS Encoding Standard OGC 08–007r1, Open Geospatial Consortium Inc. Accessed at http://www.opengeospatial.org/Google Scholar
Peel, R. (2001). Airport, navigation aid and IFR intersection data in FlightGear. FlightGear Development Documents. Accessed at http://www.flightgear.org/Docs/AirNav/AptNavFAQ.FlightGear.htmlGoogle Scholar
Peel, R. (2009). X-Plane Airport Data (Apt.Dat) file epecification, edition 850. Accessed at http://data.x-plane.com/file_specs/XP\%20APT850\%20Spec.pdfGoogle Scholar
Rodrigues, C., Silva, D.C., Rossetti, R.J.F., & Oliveira, E. (2015). Distributed flight simulation environment using Flight Simulator X. Proc. 10th Iberian Conf. Information Systems and Technologies, pp. 1293–1297, Águeda, Portugal, June 17–20.Google Scholar
Santos, A. (2010). Autonomous intelligent vehicle adaptation and performance analysis in Flight Simulator X. Master's thesis. University of Porto.Google Scholar
Schweiger, R., Brumhard, M., Hoelzer, S., & Dudeck, J. (2005). Implementing health care systems using XML standards. International Journal of Medical Informatics 74(2), 267–277.Google Scholar
Silva, D.C., Abreu, P.H., Reis, L.P., & Oliveira, E. (2014). Development of a flexible language for mission description for multi-robot missions. Information Sciences 288, 27–44.Google Scholar
Silva, D.C., Abreu, P.H., Reis, L.P., & Oliveira, E. (2015). Development of a flexible language for disturbance description for multi-robot missions. Journal of Simulation. Advance online publication. doi:10.1057/jos.2015.4.Google Scholar
Sousa, P.D. (2010). Autonomous air traffic control for intelligent vehicles using Microsoft Flight Simulator X. Master's thesis. University of Porto.Google Scholar
Sousa, P.D., Silva, D.C., & Reis, L.P. (2010). Air traffic control with Microsoft Flight Simulator X. Proc. 5th Iberic Conf. Information Systems and Technologies (CISTI 2010), pp. 378–383, Santiago de Compostela, Spain, June 16–19.Google Scholar
Web3D Consortium. (2008). Extensible 3D (X3D). ISO Standard ISO/IEC 19775–1:2008, Web3D Consortium, Inc. Accessed at http://www.web3d.org/Google Scholar
Wittman, R.L. Jr. (2009). Defining a standard: The military scenario definition language—version 1.0 standard. Proc. 2009 Spring Simulation Multiconference (SpringSim 2009) (Wainer, G.A., Shaffer, C.A., McGraw, R.M., & Chinni, M.J., Eds.). San Diego, CA: SCS/ACM.Google Scholar