Robotic Technology in Military Applications: Insights from Portuguese Navy Research

Authors

  • Nuno Pessanha Santos Portuguese Military Academy (Academia Militar) https://orcid.org/0000-0002-8079-9451
  • Victor Lobo Portuguese Navy Research Center (CINAV), Portuguese Naval Academy, Almada, Portugal

DOI:

https://doi.org/10.3849/aimt.01901

Keywords:

Robotics, Military Robotics, Research and development, Technological innovation, Military

Abstract

Robots have been used in a military context for a long time. In recent years, the pace of introducing new systems has increased for several reasons, including the widespread use of robots in civilian applications and the consequent development of a vibrant industrial base. However, adapting robot technology to military applications is not always trivial, and a good interaction between industry and military institutions is key to success. In this paper, we present a review of successful research projects undertaken by our team at the Portuguese Navy (PoN) Research Center in close collaboration with industry. We provide valuable insights that can guide future developments in this field. It is essential to guarantee continuous research and development in the military domain since the obtained knowledge is critical and undoubtedly essential to guide the future. Combining knowledge and capacity for action is crucial for continuously improving robotics, and military robotics is no exception.

Author Biographies

  • Nuno Pessanha Santos, Portuguese Military Academy (Academia Militar)

    Portuguese Military Research Center (CINAMIL), Portuguese Military Academy, Lisbon, Portugal
    Institute for Systems and Robotics (ISR), Instituto Superior T´ecnico (IST), Lisbon, Portugal
    Portuguese Navy Research Center (CINAV), Portuguese Naval Academy, Almada, Portugal

  • Victor Lobo, Portuguese Navy Research Center (CINAV), Portuguese Naval Academy, Almada, Portugal

    Portuguese Navy Research Center (CINAV), Portuguese Naval Academy, Almada, Portugal
    NOVA Information Management School (Nova IMS), Universidade Nova de Lisboa, Portugal

References

CHIN, W. Technology, War and the State: Past, Present and Future. International Affairs, 2019, 95(4), pp. 765-783. DOI 10.1093/ia/iiz106.

RUTTAN, V.W. Is War Necessary for Economic Growth?: Military Procurement and Technology Development. Oxford University Press, 2006. DOI 10.1093/0195188047.001.0001.

SULLIVAN, P.L., B.F. TESSMAN and X. LI. US Military Aid and Recipient State Cooperation. Foreign Policy Analysis, 2011, 7(3), pp. 275-294. DOI 10.1111/j.17438594.2011.00138.x.

OAKEY, R.P. Funding Innovation and Growth in UK New Technology-Based Firms: Some Observations on Contributions from the Public and Private Sectors. Venture Capital: An International Journal of Entrepreneurial Finance, 2003, 5(2), pp. 161179. DOI 10.1080/1369106032000097049.

JAVAID, M., A. HALEEM, R.P. SINGH and R. SUMAN. Substantial Capabilities of Robotics in Enhancing Industry 4.0 Implementation. Cognitive Robotics, 2021, 1, pp. 58-75. DOI 10.1016/j.cogr.2021.06.001.

RAVICHANDAR, H., A.S. POLYDOROS, S. CHERNOVA and A. BILLARD. Recent Advances in Robot Learning from Demonstration. Annual Review of Control,Robotics, and Autonomous Systems, 2020, 3, pp. 297-330. DOI 10.1146/annurevcontrol-100819-063206.

GORDON, L.A., M.P. LOEB, W. LUCYSHYN and L. ZHOU. Increasing Cybersecurity Investments in Private Sector Firms. Journal of Cybersecurity, 2015, 1(1), pp. 3-17. DOI 10.1093/cybsec/tyv011.

KAUR, J. and K.R. RAMKUMAR. The Recent Trends in Cyber Security: A Review. Journal of King Saud University - Computer and Information Sciences, 2022, 34(8), pp. 5766-5781. DOI 10.1016/j.jksuci.2021.01.018.

DESHPANDE, A. Assessing the Quantum-Computing Landscape. Communications of the ACM, 2022, 65(10), pp. 57-65. DOI 10.1145/3524109.

PIRANDOLA, S. et al. Advances in Quantum Cryptography. Advances in Optics and Photonics, 2020, 12(4), pp. 1012-1236. DOI 10.1364/AOP.361502.

MAGHAZEI, O., M.A. LEWIS and T.H. NETLAND. Emerging Technologies and the Use Case: A Multi-Year Study of Drone Adoption. Journal of Operations Management, 2022, 68(6-7), pp. 560-591. DOI 10.1002/joom.1196.

CHOI, T.-M., S. KUMAR, X. YUE and H.-L. CHAN. Disruptive Technologies and Operations Management in the Industry 4.0 Era and Beyond. Production and Operations Management, 2022, 31(1), pp. 9-31. DOI 10.1111/poms.13622.

COSTA, J. et al. 2022 Edition of the Large Scale Exercise REPMUS: Field Report. In: OCEANS 2023. Limerick: IEEE, 2023, pp. 1-6. DOI 10.1109/OCEANSLimerick52467.2023.10244531.

RIZZUTO, E. and V. RUGGIERO. Remote Passive Acoustic Barrier with Maritime Unmanned Systems: Preliminary Tests During REPMUS-21. In: Technology and Science for the Ships of the Future: Proceedings of NAV 2022: 20th International Conference on Ship & Maritime Research. Vol. 6. IOS Press. 2022, pp. 287-294. DOI 10.3233/PMST220036.

NUNES, I. and M. SIMÕES-MARQUES. SINGRAR Usability Study. In: Design, User Experience, and Usability. Design Philosophy, Methods, and Tools: Second International Conference, DUXU 2013, Proceedings, Part I 2. Berlin: Springer, 2013, pp. 359-368. DOI 10.1007/978-3-642-39229-0 39.

SIMÕES-MARQUES, M.J. and F.J. PIRES. SINGRAR – A Fuzzy Distributed Expert System to Assist Command and Control Activities in Naval Environment. European Journal of Operational Research, 2003, 145(2), pp. 343-362. DOI 10.1016/S0377-2217(02)00541-6.

SIMÕES-MARQUES, M. SINGRAR — A Distributed Expert System for Emergency Management: Context and Design. Real-World Decision Support Systems: Case Studies, 2016, pp. 243-274. DOI 10.1007/978-3-319-43916-7 11.

Instituto Universitário Militar [online]. [Viewed 2023-12-01]. Available from: https://www.ium.pt/

ANTUNES, T.L., N. PESSANHA SANTOS, R.P. MOURA and V. LOBO. Sea Pollution: Analysis and Monitoring Using Unmanned Vehicles. In: 2023 IEEE Underwater Technology (UT). 2023, pp. 1-8. DOI 10.1109/UT49729.2023.10103429.

PESSANHA SANTOS, N., V. LOBO and A. BERNARDINO. Autoland Project: Fixed-Wing UAV Landing on a Fast Patrol Boat Using Computer Vision. In: OCEANS 2019. Seatle: IEEE, 2019, pp. 1-5. DOI 10.23919/OCEANS40490.2019.8962869.

PESSANHA SANTOS, N., V. LOBO and A. BERNARDINO. Directional Statistics for 3D Model-Based UAV Tracking. IEEE Access, 2020, 8, pp. 33884-33897. DOI 10.1109/ACCESS.2020.2973970.

PESSANHA SANTOS, N., V. LOBO and A. BERNARDINO. Unscented Particle Filters with Refinement Steps for UAV Pose Tracking. Journal of Intelligent&Robotic Systems, 2021, 102(2), p. 52. DOI 10.1007/s10846-021-01409-y.

PESSANHA SANTOS, N., V. LOBO and A. BERNARDINO. Two-Stage 3D ModelBased UAV Pose Estimation: A Comparison of Methods for Optimization. Journal of Field Robotics, 2020, 37(4), pp. 580-605. DOI 10.1002/rob.21933.

MARQUES, M.M. et al. Unmanned Aircraft Systems in Maritime Operations: Challenges Addressed in the Scope of the SEAGULL Project. In: OCEANS 2015. Genova: IEEE, 2015, pp. 1-6. DOI 10.1109/OCEANS-Genova.2015.7271427.

PESSANHA SANTOS, N., V.B. RODRIGUES, A.B. PINTO and B. DAMAS. Automatic Detection of Civilian and Military Personnel in Reconnaissance Missions Using a UAV. In: 2023 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC). 2023, pp. 157-162. DOI 10.1109/ICARSC58346.2023.10129575.

MARQUES, M.M., R.S. CARAPAU, A.V. RODRIGUES, V. LOBO, J. GOUVEIACARVALHO, W. ANTUNES, T. GONÇALVES, F. DUARTE and B. VERÍSSIMO. GammaEx Project: A Solution for CBRN Remote Sensing Using Unmanned Aerial Vehicles in Maritime Environments [online]. 2017 [viewed 2023-12-05]. Available from: https://ieeexplore.ieee.org/abstract/document/8232258/

MORAIS, F., T. RAMALHO, P. SINOGAS, M.M. MARQUES, N. PESSANHA SANTOS and V. LOBO. Trajectory and Guidance Mode for Autonomously Landing an UAV on a Naval Platform Using a Vision Approach. In: OCEANS 2015 - Genova. Genova: IEEE, 2015, pp. 1-7. DOI 10.1109/OCEANS-Genova.2015.7271423.

PESSANHA SANTOS, N., V. LOBO and A. BERNARDINO. Particle Filtering Based Optimization Applied to 3D Model-Based Estimation for UAV Pose Estimation. In: OCEANS 2017 - Aberdeen. 2017, pp. 1-10. DOI 10.1109/OCEANSE.2017. 8084783.

PESSANHA SANTOS, N., V. LOBO and A. BERNARDINO. 3D Model-Based UAV Pose Estimation Using GPU. In: OCEANS 2019 MTS/IEEE Seattle. 2019, pp. 1-6. DOI 10.23919/OCEANS40490.2019.8962704.

PESSANHA SANTOS, N., V. LOBO and A. BERNARDINO. A Ground-Based Vision System for UAV Tracking. In: OCEANS 2015 - Genova. 2015, pp. 1-9. DOI 10.1109/OCEANS-Genova.2015.7271349.

PESSANHA SANTOS, N., V. LOBO and A. BERNARDINO. Unmanned Aerial Vehicle Tracking Using a Particle Filter Based Approach. In: 2019 IEEE Underwater Technology (UT). 2019, pp. 1-10. DOI 10.1109/UT.2019.8734465.

PESSANHA SANTOS, N., V. LOBO and A. BERNARDINO. 3D Model-Based Estimation for UAV Tracking. In: OCEANS 2018 MTS/IEEE Charleston. 2018, pp. 1-9. DOI 10.1109/OCEANS.2018.8604539.

PESSANHA SANTOS, N., V. LOBO and A. BERNARDINO. Fixed-Wing Unmanned Aerial Vehicle 3D-Model-Based Tracking for Autonomous Landing. Drones, 2023, 7(4). DOI 10.3390/drones7040243.

GOUVEIA-CARVALHO, J., W.T. ANTUNES, T. GONÇALVES, V. LOBO, F. DUARTE, B. VERÍSSIMO, A. BAPTISTA and M.M. MARQUES. Chemical and Radiological Sensors Integration in Unmanned Aerial Systems with ATEX Compliance. Key Engineering Materials, 2021, 893, pp. 17-27. DOI 10 . 4028 / www.scientific.net/KEM.893.17.

PESSANHA SANTOS, N. Fixed-Wing UAV Pose Estimation Using a SelfOrganizing Map and Deep Learning. Robotics, 2024, 13(8). DOI 10.3390/robotics13080114.

MONTEIRO MARQUES, M. et al. Assessment of a Shallow Water Area in the Tagus Estuary Using Unmanned Underwater Vehicle (or AUV’s), Vector-Sensors, Unmanned Surface Vehicles, and Hexacopters - REX’17. In: 2018 OCEANS. Kobe: IEEE, 2018, pp. 1-5. DOI 10.1109/OCEANSKOBE.2018.8559177.

MAGALHÃES, J., B. DAMAS and V. LOBO. Reinforcement Learning: The Application to Autonomous Biomimetic Underwater Vehicles Control. In: IOP Conference Series: Earth and Environmental Science. Vol. 172. 1. IOP Publishing. 2018, pp. 1-6. DOI 10.1088/1755-1315/172/1/012019.

ANTÓNIO, T.G., P.P. SILVA, B. DAMAS and M.B. MOREIRA. Modeling and Simulation of a Biomimetic Underwater Vehicle. In: 2022 7th International Conference on Mechanical Engineering and Robotics Research (ICMERR). IEEE. 2022, pp. 118123. DOI 10.1109/ICMERR56497.2022.10097824.

COSTA, R.N., P.A. PIRES DA SILVA and M.Á. MOREIRA. Challenges of the Design and Construction of the Portuguese Naval Academy Modular Multimission Unmanned Surface Vehicle (PoNA MM-USV) [online]. 2019-10, D023S005R001 [viewed 2023-12-05]. Available from: https : / / onepetro . org / SNAMESMC / proceedings - pdf / SMC19 / 2 - MC19 / D023S005R001 / 1137125 / sname - smc - 2019 059.pdf

MARTINS, A. et al. Field Experiments for Marine Casualty Detection with Autonomous Surface Vehicles. In: 2013 OCEANS. San Diego: IEEE, 2013, pp. 1-5. DOI 10.23919/OCEANS.2013.6741348.

DIAS, A.R., N. PESSANHA SANTOS and V. LOBO. Implementation of a Passive Acoustic Barrier for Surveillance. In: OCEANS 2023 - Limerick. IEEE, 2023, pp. 1-6. DOI 10.1109/OCEANSLimerick52467.2023.10244682.

TAKAYAMA, L., W. JU and C. NASS. Beyond Dirty, Dangerous and Dull: What Everyday People Think Robots Should Do. In: Proceedings of the 3rd ACM/IEEE International Conference on Human Robot Interaction. 2008, pp. 25-32. DOI 10 . 1145/1349822.1349827.

FISHEL, J.A., T. OLIVER, M. EICHERMUELLER, G. BARBIERI, E. FOWLER, T. HARTIKAINEN, L. MOSS and R. WALKER. Tactile Telerobots for Dull, Dirty, Dangerous, and Inaccessible Tasks. In: 2020 IEEE International Conference on Robotics and Automation (ICRA). IEEE. 2020, pp. 11305-11310. DOI 10.1109/ICRA40945.2020.9196888.

SHARKEY, N.E. The Evitability of Autonomous Robot Warfare. International Review of the Red Cross, 2012, 94(886), pp. 787-799. DOI 10.1017/S1816383112000732.

FERREIRA, H., C. ALMEIDA, A. MARTINS, J. ALMEIDA, N. DIAS, A. DIAS and E. SILVA. Autonomous Bathymetry for Risk Assessment with ROAZ Robotic Surface Vehicle. In: Oceans 2009-Europe. IEEE. 2009, pp. 1-6. DOI 10.1109/OCEANSE.2009.5278235.

DUNBABIN, M. and L. MARQUES. Robots for Environmental Monitoring: Significant Advancements and Applications. IEEE Robotics & Automation Magazine, 2012, 19(1), pp. 24-39. DOI 10.1109/MRA.2011.2181683.

COUCEIRO, M.S. An Overview of Swarm Robotics for Search and Rescue Applications. Artificial Intelligence: Concepts, Methodologies, Tools, and Applications, 2017, pp. 1522-1561. DOI 10.4018/978-1-5225-1759-7.ch061.

TADJDEH, Y. Navy Sees Littoral Combat Ship as Robotic Systems Platform. National Defense [online]. 2017 [viewed 2023-12-20]. Available from: https://www.jstor.org/stable/27021643

YEONG, D.J., G. VELASCO-HERNANDEZ, J. BARRY and J. WALSH. Sensor and Sensor Fusion Technology in Autonomous Vehicles: A Review. Sensors, 2021, 21(6), p. 2140. DOI 10.3390/s21062140.

KOCIĆ, J., N. JOVIČIĆ and V. DRNDAREVIĆ. Sensors and Sensor Fusion in Autonomous Vehicles. In: 2018 26th Telecommunications Forum (TELFOR). IEEE. 2018, pp. 420-425. DOI 10.1109/TELFOR.2018.8612054.

PONGPUNWATTANA, A. and R. RYSDYK. Real-Time Planning for Multiple Autonomous Vehicles in Dynamic Uncertain Environments. Journal of Aerospace Computing, Information, and Communication, 2004, 1(12), pp. 580-604. DOI 10.2514/1. 12919.

ASMARE, E., A. GOPALAN, M. SLOMAN, N. DULAY and E. LUPU. A Mission Management Framework for Unmanned Autonomous Vehicles. In: MobileWireless Middleware, Operating Systems, and Applications: Second International Conference, Mobilware 2009, Berlin, Germany, April 28-29, 2009 Proceedings 2. Springer. 2009, pp. 222-235. DOI 10.1007/978-3-642-01802-2 17.

PESSANHA SANTOS, N. Hydrogen in the Portuguese Navy: A Case Study. International Journal of Hydrogen Energy, 2022, 47(66), pp. 28684-28698. ISSN 03603199. DOI https://doi.org/10.1016/j.ijhydene.2022.06.180.

ROSS, C. and S. GUHATHAKURTA. Autonomous Vehicles and Energy Impacts: A Scenario Analysis. Energy Procedia, 2017, 143, pp. 47-52. DOI 10.1016/j.egypro. 2017.12.646.

URAGUN, B. Energy Efficiency for Unmanned Aerial Vehicles. In: 2011 10th International Conference on Machine Learning and Applications and Workshops. Vol. 2. IEEE. 2011, pp. 316-320. DOI 10.1109/ICMLA.2011.159.

MAHMOUD ZADEH, S., D.M. POWERS and R. BAIRAM ZADEH. Autonomy and Unmanned Vehicles. Cognitive Science and Technology, 2019, 116. DOI 10.1007/978-981-13-2245-7.

DURST, P.J. and M.W. GRAY. Levels of Autonomy and Autonomous System Performance Assessment for Intelligent Unmanned Systems [online]. 2014 [viewed 202312-05]. Available from: http://hdl.handle.net/11681/3284

BURMEISTER, H.-C., W.C. BRUHN, Ø.J. RØDSETH and T. PORATHE. Can Unmanned Ships Improve Navigational Safety? In: Proceedings of the Transport Research Arena, TRA 2014, 14-17 April 2014, Paris [online]. 2014 [viewed 2023-1212]. Available from: https://research.chalmers.se/en/publication/198207

LEE, J.-G., K.J. KIM, S. LEE and D.-H. SHIN. Can Autonomous Vehicles Be Safe and Trustworthy? Effects of Appearance and Autonomy of Unmanned Driving Systems. International Journal of Human-Computer Interaction, 2015, 31(10), pp. 682691. DOI 10.1080/10447318.2015.1070547.

DE CUBBER, G., D. DOROFTEI, D. SERRANO, K. CHINTAMANI, R. SABINO and S. OUREVITCH. The EU-ICARUS Project: Developing Assistive Robotic Tools for Search and Rescue Operations. In: 2013 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR). Linköping: IEEE, 2013, pp. 1-4. DOI 10.1109/SSRR.2013.6719323.

DE CUBBER, G., D. SERRANO, K. BERNS, K. CHINTAMANI, R. SABINO, S. OUREVITCH, D. DOROFTEI, C. ARMBRUST, T. FLAMMA and Y. BAUDOIN. Search and Rescue Robots Developed by the European ICARUS Project [online]. 2013 [viewed 2023-12-05]. Available from: http://mecatron.rma.ac.be/pub/2013/Search%20and%20Rescue%20robots%20developed%20by%20the%20European%20ICARUS%20project%20-%20Article.pdf

MATOS, A. et al. Unmanned Maritime Systems for Search and Rescue. Search and Rescue Robotics - From Theory to Practice, 2017, pp. 77-92. DOI 10.5772/intechopen.69492.

BOGUE, R. Search and Rescue and Disaster Relief Robots: Has Their Time Finally Come? Industrial Robot: An International Journal, 2016, 43(2), pp. 138-143. DOI 10.1108/IR-12-2015-0228.

RIBEIRO, R., G. CRUZ, J. MATOS and A. BERNARDINO. A Data Set for Airborne Maritime Surveillance Environments. IEEE Transactions on Circuits and Systems for Video Technology, 2017, 29(9), pp. 2720-2732. DOI 10.1109/TCSVT.2017.2775524.

CSERNATONI, R. Constructing the EU’s High-Tech Borders: FRONTEX and DualUse Drones for Border Management. European Security, 2018, 27(2), pp. 175-200. DOI 10.1080/09662839.2018.1481396.

BAIRD, T. Surveillance Design Communities in Europe: A Network Analysis. Surveillance & Society, 2016, 14(1), pp. 34-58. DOI 10.24908/ss.v14i1.5622.

CARAPAU, R.S., A.V. RODRIGUES, M.M. MARQUES, V. LOBO and F. COITO. Interoperability of Unmanned Systems in Military Maritime Operations: Developing a Controller for Unmanned Aerial Systems Operating in Maritime Environments. In: OCEANS 2017-Aberdeen. IEEE. 2017, pp. 1-7. DOI 10.1109/OCEANSE.2017.8084862.

MARCIN, M., S. ADAM, Z. JERZY and M. MARCIN. Fish-Like Shaped Robot for Underwater Surveillance and Reconnaissance-Hull Design and Study of Drag and Noise. Ocean Engineering, 2020, 217, p. 107889. DOI 10.1016/j.oceaneng.2020.107889.

LAMBERT, A. Geostrategic Shifts and Their Impact on the Indo-Pacific Region [online]. 2022 [viewed 2023-12-08]. Available from: https://www.taylorfrancis.com/chapters/edit/10.4324/9781003354703-2/

CSURGAI, G. Geopolitics, Geostrategy and Geoeconomics: Reflections on the Changing Force Factors in the International System. Recent Geopolitical Trends in Eurasia, 2021, p. 13. DOI 10.33917/es-3.169.2020.30-41.

PESSANHA SANTOS, N. The Expansion of Data Science: Dataset Standardization. Standards, 2023, 3(4), pp. 400-410. ISSN 2305-6703. DOI 10.3390/standards3040028.

MARQUES, M.M., R. MENDONÇA, F. MARQUES, T. RAMALHO, V. LOBO, A. MATOS, B. FERREIRA, N. SIMÕES and I. CASTELÃO. REX 16 - Robotic Exercises 2016 Multi-Robot Field Trials. In: 2019 IEEE Underwater Technology (UT). Kaohsiung: IEEE, 2019, pp. 1-5. DOI 10.1109/UT.2019.8734390.

MARQUES, M.M., A. MARTINS, A. MATOS, N. CRUZ, J.M. ALMEIDA, J.C. ALVES, V. LOBO and E. SILVA. REX 2014 - Robotic Exercises 2014 Multi-Robot Field Trials. In: OCEANS 2015-MTS/IEEE Washington. IEEE. 2015, pp. 1-6. DOI 10.23919/OCEANS.2015.7404497.

PIEDADE, J. and P. SIMÕES. The Importance of Creating a Technological Free Zone [online]. 2023. Available from: https://science- society.inesctec.pt/index.php/inesctecesociedade/article/view/116

JAMSHIDI, M., ed. System of Systems Engineering: Innovations for the 21st Century. Hoboken: Wiley, 2009. DOI 10.1002/9780470403501.

PLATTS, J., M. CUMMINGS and R. KERR. Applicability of STANAG 4586 to Future Unmanned Aerial Vehicles. In: AIAA Infotech@ Aerospace 2007 Conference and Exhibit. California, 2007, p. 2753. DOI 10.2514/6.2007-2753.

KHAN, N.A., N. JHANJHI, S.N. BROHI and Z.A. ALMUSAYLIM. Proposing an Algorithm for UAVs Interoperability: MAVLink to STANAG 4586 for SecuringCommunication. In: Intelligent Computing and Innovation on Data Science: Proceedings of ICTIDS 2021. Springer. 2021, pp. 413-423. DOI 10.1007/978-981-163153-5 44.

KREITMAIR, T., J. ROSS, T. SKAAR and N.C. COMMAND. Experimentation Activities with Aerospace Ground Surveillance. In: Proceedings of the Command and Control Research and Technology Symposium (CCRTS) [online]. 2005 [viewed 202312-05]. Available from: https://www.dodccrp.org/events/10th ICCRTS/CD/papers/023.pdf

PRIVETT, G.J., P.R.W. HARVEY, D.M. BOOTH, P.J. KENT, N.J. REDDING, D. EVANS and K.L. JONES. Software Tools or Assisting the Multisource Imagery Analyst. In: Applications of Digital Image Processing XXVI. Vol. 5203. SPIE. 2003, pp. 163-176. DOI 10.1117/12.510037.

SULLIVAN, P.L., N.J. HASTAD and R.E. POLLMANN. STANAG 4575: What It Is and How It Works. In: Airborne Reconnaissance XXVI. Vol. 4824. SPIE. 2002, pp. 78-87. DOI 10.1117/12.451989.

BEAULNE, P.D. The Addition of Enhanced Capabilities to NATO GMTIF STANAG 4607 to Support RADARSAT-2 GMTI Data [online]. 2007. Defence R&D CanadaOttawa, Technical Memorandum DRDC Ottawa TM 2007-323 [viewed 2023-12-29]. Available from: https://archive.org/details/DTIC ADA479333

BUŘITA, L., J. HRABOVSKÝ, A. NOVÁK and P. POHANKA. Systems Integration in Military Environment. Advances in Military Technology, 2020, 15(1), pp. 25-42. DOI 10.3849/aimt.01334.

PECKHAM, H.M. A STANAG for NATO Imagery Interoperable Data Links. In: Airborne Reconnaissance XVII. Vol. 2023. SPIE. 1993, pp. 13-20. DOI 10.1117/12.165536.

KAYAYURT, B. and İ. YAYLA. Application of STANAG 4586 Standard for Turkish Aerospace Industries UAV Systems. In: 2013 IEEE/AIAA 32nd Digital Avionics Systems Conference (DASC). East Syracuse: IEEE, 2013, 4B4-7. DOI 10.1109/DASC. 2013.6719665.

SZABOLCSI, R. Beyond Training Minimums - A New Concept of the UAV Operator Training Program. In: International Conference Knowledge-Based Organization. Vol. 22. 3. 2016, pp. 560-566. DOI 10.1515/kbo-2016-0096.

SZABOLCSI, R. UAV Operator Training - Beyond Minimum Standards. In: Scientific Research And Education in the Air Force. Vol. 18. 1. 2016, pp. 193-198. DOI 10.19062/2247-3173.2016.18.1.25.

RODRIGUES, A.V., R.S. CARAPAU, M.M. MARQUES, V. LOBO and F. COITO. Unmanned Systems Interoperability in Military Maritime Operations: MAVLink to STANAG 4586 Bridge. In: OCEANS 2017-Aberdeen. IEEE. 2017, pp. 1-5. DOI 10.1109/OCEANSE.2017.8084866.

MARQUES, M. Reference Model for Interoperability of Autonomous Systems. [online]. viewed [2023-12-10]. 2018. Available from: http://hdl.handle.net/10362/57144

SILVEIRA, J.T., T. FIDALGO DE FREITAS, G. FABIÃO and M. ASSIS RAIMUNDO. The Simplification of Procedures in Portuguese Administrative Law. Administrative Sciences, 2022, 12(1), pp. 1-18. DOI 10.3390/admsci12010009.

Downloads

Published

16-06-2025

Issue

Section

Case study

Categories

How to Cite

Pessanha Santos, N., & Lobo, V. (2025). Robotic Technology in Military Applications: Insights from Portuguese Navy Research. Advances in Military Technology, 20(1), 21-38. https://doi.org/10.3849/aimt.01901

Similar Articles

11-20 of 209

You may also start an advanced similarity search for this article.