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KBRN Dekontaminasyonunda Sürü Robotları: Verimlilik ve Güvenliği Arttırmak

Year 2023, Volume: 4 Issue: 2, 72 - 81, 24.12.2023
https://doi.org/10.58769/joinssr.1362574

Abstract

Bu makalede, akıllı robotlarının KBRN (Kimyasal, Biyolojik, Radyolojik ve Nükleer) dekontaminasyon süreçlerine entegrasyonunu araştırılmıştır. İşbirlikçi ve merkezi olmayan yapılarıyla bilinen akıllı robotlar, dekontaminasyon operasyonlarının verimliliğini ve güvenliğini artırma konusunda umut vaat etmektedir. Çalışmamız, akıllı robotları ve KBRN dekontaminasyonuna genel bir bakış sunmakta ve bu kritik görevle ilgili zorlukları ve gereksinimleri vurgulamaktadır. KBRN dekontaminasyonunda akıllı robotların özel uygulamalarını ele almaktadır. Tasarım hususları, operasyonel yönleri ve sürece getirdikleri avantajları tartışılmıştır. Akıllı robot sistemlerinin etkinliğini değerlendirmek için çeşitli senaryoları kapsayan gerçek dünya vaka çalışmaları sunulmuştur. Ayrıca, bu alandaki kalan zorluklar ele alınmış ve gelişmekte olan teknolojileri ve teknikleri belirleyerek gelecekteki yönleri keşfedilmiştir. Araştırmamız, mevcut bilgi tabanına katkıda bulunmayı, sürü robot tabanlı KBRN dekontaminasyonunun daha iyi anlaşılmasını sağlamayı ve bu gelişen alanda daha fazla ilerlemeye teşvik etmeyi amaçlamaktadır.

References

  • [1] León, J., Cardona, G., Botello, A., & Calderón, J. (2019). Robot Swarms Theory Applicable to Seek and Rescue Operation. , 1061-1070. https://doi.org/10.1007/978-3-319-53480-0_104.
  • [2] García, R., Iglesia, D., Paz, J., Leithardt, V., & Villarrubia, G. (2021). Urban Search and Rescue with Anti-pheromone Robot Swarm architecture. 2021 Telecoms Conference (ConfTELE), 1-6. https://doi.org/10.1109/ConfTELE50222.2021.9435557.
  • [3] Wang, Q., & Zhang, L. (2021). External Power-Driven Microrobotic Swarm: From Fundamental Understanding to Imaging-Guided Delivery.. ACS nano. https://doi.org/10.1021/acsnano.0c07753.
  • [4] Bakhshipour, M., Ghadi, M., & Namdari, F. (2017). Swarm robotics search & rescue: A novel artificial intelligence-inspired optimization approach. Appl. Soft Comput., 57, 708-726. https://doi.org/10.1016/j.asoc.2017.02.028.
  • [5] Tang, Q., Xu, Z., Yu, F., Zhang, Z., & Zhang, J. (2019). Dynamic target searching and tracking with swarm robots based on stigmergy mechanism. Robotics Auton. Syst., 120. https://doi.org/10.1016/J.ROBOT.2019.103251.
  • [6] Yang, B., Ding, Y., Jin, Y., & Hao, K. (2015). Self-organized swarm robot for target search and trapping inspired by bacterial chemotaxis. Robotics Auton. Syst., 72, 83-92. https://doi.org/10.1016/j.robot.2015.05.001.
  • [7] Zheng, Z., Li, J., Li, J., & Tan, Y. (2014). Improved group explosion strategy for searching multiple targets using swarm robotics. 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 246-251. https://doi.org/10.1109/SMC.2014.6973915.
  • [8] Balta, H., Bedkowski, J., Govindaraj, S., Majek, K., Musialik, P., Serrano, D., ... & De Cubber, G. (2017). Integrated data management for a fleet of search‐and‐rescue robots. Journal of Field Robotics, 34(3), 539-582.
  • [9] Bayindir, L., & Şahin, E. (2007). A review of studies in swarm robotics. Turkish Journal of Electrical Engineering & Computer Sciences, 15(2), 115-147.
  • [10] Gent, N., & Milton, R. (2018). Chemical, biological, radiological and nuclear incidents: clinical management and health protection. Publ Health Engl.
  • [11] Guchua, A. (2023). NATO’S ROLE IN THE POLICY OF NON-PROLIFERATION OF WEAPONS OF MASS DESTRUCTION AND GLOBAL SECURITY: A SHORT OVERVIEW. Journal of Liberty and International Affairs, 9(2), 495-506.
  • [12] Currie, J., & Heslop, D. (2018). Operational systems evaluation of a large scale multi-agency decontamination exercise. International Journal of Disaster Risk Reduction. https://doi.org/10.1016/J.IJDRR.2018.03.027.
  • [13] Kacer, P., Švrček, J., Syslová, K., Václavík, J., Pavlík, D., Červený, J., & Kuzma, M. (2012). Vapor Phase Hydrogen Peroxide – Method for Decontamination of Surfaces and Working Areas from Organic Pollutants. . https://doi.org/10.5772/33451.
  • [14] Lipp, M., Jaehnichen, G., Golecki, N., Fecht, G., Reichl, R., & Heeg, P. (2000). Microbiological, microstructure, and material science examinations of reprocessed Combitubes after multiple reuse.. Anesthesia and analgesia, 91 3, 693-7. https://doi.org/10.1097/00000539- 200009000-00037.
  • [15] Bayir, A., Eyi, Y., Durusu, M., Oztuna, A., & Eryilmaz, M. (2011). (P1-74) Introduction of the Portable Decontamination Unit of Gulhane Military Medical Academy. Prehospital and Disaster Medicine, 26, s122 - s123. https://doi.org/10.1017/S1049023X11004067.
  • [16] Rybka, A., Gavel, A., Pražák, P., Meloun, J., & Pejchal, J. (2019). Decontamination of CBRN units contaminated by highly contagious biological agents.. Epidemiologie, mikrobiologie, imunologie : casopis Spolecnosti pro epidemiologii a mikrobiologii Ceske lekarske spolecnosti J.E. Purkyne, 68 1, 40-45.
  • [17] Zhang, Y., Yan, K., Ji, F., & Zhang, L. (2018). Enhanced Removal of Toxic Heavy Metals Using Swarming Biohybrid Adsorbents. Advanced Functional Materials, 28. https://doi.org/10.1002/adfm.201806340.
  • [18] Xue, S. D., & Zeng, J. C. (2008). Control over swarm robots search with swarm intelligence principles. Journal of System Simulation, 20(13), 3449-3454.
  • [19] Wood, R. J., Nagpal, R., & Wei, G. Y. (2013). Flight of the RoboBees. Scientific American, 308(3), 60-65. https://doi.org/10.1038/scientificamerican0313-60
  • [20] Ma, K. Y., Chirarattananon, P., Fuller, S. B., & Wood, R. J. (2013). Controlled flight of a biologically inspired, insect-scale robot. Science, 340(6132), 603-607. https://doi.org/10.1126/science.1231806
  • [21] Hilder, J., Naylor, R., Rizihs, A., Franks, D., & Timmis, J. (2014). The Pi Swarm: A Low-Cost Platform for Swarm Robotics Research and Education. , 151-162. https://doi.org/10.1007/978-3-319-10401-0_14.
  • [22] Schranz, M., Umlauft, M., Sende, M., & Elmenreich, W. (2020). Swarm robotic behaviors and current applications. Frontiers in Robotics and AI, 7, 36. https://doi.org/10.3389/frobt.2020.00036
  • [23] Saska, M., Vonásek, V., Chudoba, J., Thomas, J., Loianno, G., & Kumar, V. (2016). Swarm distribution and deployment for cooperative surveillance by micro-aerial vehicles. Journal of Intelligent & Robotic Systems, 84, 469-492.
  • [24] Francesca, G., Brambilla, M., Brutschy, A., Garattoni, L., Miletitch, R., Podevijn, G., ... & Birattari, M. (2015). AutoMoDe-Chocolate: automatic design of control software for robot swarms. Swarm Intelligence, 9, 125-152.
  • [25] Kuckling, J., Van Pelt, V., & Birattari, M. (2022). AutoMoDe-Cedrata: automatic design of behavior trees for controlling a swarm of robots with communication capabilities. SN Computer Science, 3(2), 136.
  • [26] Shan, Q., & Mostaghim, S. (2020, October). Collective decision making in swarm robotics with distributed Bayesian hypothesis testing. In International Conference on Swarm Intelligence (pp. 55-67). Cham: Springer International Publishing.
  • [27] De Masi, G., & Ferrante, E. (2020, February). Quality-dependent adaptation in a swarm of drones for environmental monitoring. In 2020 Advances in Science and Engineering Technology International Conferences (ASET) (pp. 1-6). IEEE.
  • [28] Cambier, N., Albani, D., Frémont, V., Trianni, V., & Ferrante, E. (2021). Cultural evolution of probabilistic aggregation in synthetic swarms. Applied Soft Computing, 113, 108010.
  • [29] Wörn, H., Szymanski, M., & Seyfried, J. (2006). The I-SWARM project. ROMAN 2006 - The 15th IEEE International Symposium on Robot and Human Interactive Communication, 492-496. https://doi.org/10.1109/ROMAN.2006.314376.
  • [30] Li, M. (2019). Swarm Robot Task Planning Based on Air and Ground Coordination for Disaster Search and Rescue. Journal of Mechanical Engineering. https://doi.org/10.3901/jme.2019.11.001.
  • [31] Cardona, G., & Calderón, J. (2019). Robot Swarm Navigation and Victim Detection Using Rendezvous Consensus in Search and Rescue Operations. Applied Sciences. https://doi.org/10.3390/APP9081702.
  • [32] Song, Y., Liang, W., & Yang, Y. (2012). A method for grinding removal control of a robot belt grinding system. Journal of Intelligent Manufacturing, 23, 1903-1913. https://doi.org/10.1007/S10845-011-0508-6.
  • [33] Hilder, J., Naylor, R., Rizihs, A., Franks, D., & Timmis, J. (2014). The Pi Swarm: A Low-Cost Platform for Swarm Robotics Research and Education. , 151-162. https://doi.org/10.1007/978-3-319-10401-0_14.
  • [34] Duarte, M., Gomes, J., Costa, V., Rodrigues, T., Silva, F., Lobo, V., Marques, M., Oliveira, S., & Christensen, A. (2016). Application of swarm robotics systems to marine environmental monitoring. OCEANS 2016 - Shanghai, 1-8. https://doi.org/10.1109/OCEANSAP.2016.7485429.
  • [35] McGuire, K., Wagter, C., Tuyls, K., Kappen, H., & Croon, G. (2019). Minimal navigation solution for a swarm of tiny flying robots to explore an unknown environment. Science Robotics, 4. https://doi.org/10.1126/scirobotics.aaw9710.
  • [36] Ducatelle, F., Caro, G., Förster, A., Bonani, M., Dorigo, M., Magnenat, S., Mondada, F., O'Grady, R., Pinciroli, C., Rétornaz, P., Trianni, V., & Gambardella, L. (2014). Cooperative navigation in robotic swarms. Swarm Intelligence, 8, 1-33. https://doi.org/10.1007/s11721- 013-0089-4.
  • [37] Zhang, X., & Ali, M. (2020). A Bean Optimization-Based Cooperation Method for Target Searching by Swarm UAVs in Unknown Environments. IEEE Access, 8, 43850-43862. https://doi.org/10.1109/ACCESS.2020.2977499.
  • [38] Arvin, F., Murray, J., Shi, L., Zhang, C., & Yue, S. (2014). Development of an autonomous micro robot for swarm robotics. 2014 IEEE International Conference on Mechatronics and Automation, 635-640. https://doi.org/10.1109/ICMA.2014.6885771.
  • [39] Lee, W., & Kim, D. (2019). Adaptive approach to regulate task distribution in swarm robotic systems. Swarm Evol. Comput., 44, 1108- 1118. https://doi.org/10.1016/j.swevo.2018.11.005.
  • [40] Higgins, F., Tomlinson, A., & Martin, K. (2009). Survey on Security Challenges for Swarm Robotics. 2009 Fifth International Conference on Autonomic and Autonomous Systems, 307-312. https://doi.org/10.1109/ICAS.2009.62.
  • [41] Rango, F., Palmieri, N., Yang, X., & Marano, S. (2018). Swarm robotics in wireless distributed protocol design for coordinating robots involved in cooperative tasks. Soft Computing, 22, 4251-4266. https://doi.org/10.1007/s00500-017-2819-9.
  • [42] St-Onge, D., Kaufmann, M., Panerati, J., Ramtoula, B., Cao, Y., Coffey, E., & Beltrame, G. (2020). Planetary Exploration With Robot Teams: Implementing Higher Autonomy With Swarm Intelligence. IEEE Robotics & Automation Magazine, 27, 159-168. https://doi.org/10.1109/MRA.2019.2940413.
  • [43] Johnson, M., & Brown, D. (2016). Evolving and Controlling Perimeter, Rendezvous, and Foraging Behaviors in a Computation-Free Robot Swarm. EAI Endorsed Trans. Collab. Comput., 2, e5. https://doi.org/10.4108/eai.3-12-2015.2262390.

Swarm Robots in CBRN Decontamination: Enhancing Efficiency and Safety

Year 2023, Volume: 4 Issue: 2, 72 - 81, 24.12.2023
https://doi.org/10.58769/joinssr.1362574

Abstract

In this paper, we explore the integration of swarm robots in CBRN (Chemical, Biological, Radiological, and Nuclear) decontamination processes. Swarm robots, known for their collaborative and decentralized nature, hold promise in improving the efficiency and safety of decontamination operations. Our study provides an overview of swarm robots and CBRN decontamination, highlighting the challenges and requirements associated with this critical task. We delve into the specific applications of swarm robots in CBRN decontamination, discussing their design considerations, operational aspects, and the advantages they bring to the process. To evaluate the efficacy of swarm robot systems, we present real-world case studies encompassing various scenarios. Furthermore, we address the remaining challenges in this field and explore future directions by identifying emerging technologies and techniques. Our research aims to contribute to the existing knowledge base, fostering a deeper understanding of swarm robot based CBRN decontamination and inspiring further advancements in this evolving domain.

References

  • [1] León, J., Cardona, G., Botello, A., & Calderón, J. (2019). Robot Swarms Theory Applicable to Seek and Rescue Operation. , 1061-1070. https://doi.org/10.1007/978-3-319-53480-0_104.
  • [2] García, R., Iglesia, D., Paz, J., Leithardt, V., & Villarrubia, G. (2021). Urban Search and Rescue with Anti-pheromone Robot Swarm architecture. 2021 Telecoms Conference (ConfTELE), 1-6. https://doi.org/10.1109/ConfTELE50222.2021.9435557.
  • [3] Wang, Q., & Zhang, L. (2021). External Power-Driven Microrobotic Swarm: From Fundamental Understanding to Imaging-Guided Delivery.. ACS nano. https://doi.org/10.1021/acsnano.0c07753.
  • [4] Bakhshipour, M., Ghadi, M., & Namdari, F. (2017). Swarm robotics search & rescue: A novel artificial intelligence-inspired optimization approach. Appl. Soft Comput., 57, 708-726. https://doi.org/10.1016/j.asoc.2017.02.028.
  • [5] Tang, Q., Xu, Z., Yu, F., Zhang, Z., & Zhang, J. (2019). Dynamic target searching and tracking with swarm robots based on stigmergy mechanism. Robotics Auton. Syst., 120. https://doi.org/10.1016/J.ROBOT.2019.103251.
  • [6] Yang, B., Ding, Y., Jin, Y., & Hao, K. (2015). Self-organized swarm robot for target search and trapping inspired by bacterial chemotaxis. Robotics Auton. Syst., 72, 83-92. https://doi.org/10.1016/j.robot.2015.05.001.
  • [7] Zheng, Z., Li, J., Li, J., & Tan, Y. (2014). Improved group explosion strategy for searching multiple targets using swarm robotics. 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 246-251. https://doi.org/10.1109/SMC.2014.6973915.
  • [8] Balta, H., Bedkowski, J., Govindaraj, S., Majek, K., Musialik, P., Serrano, D., ... & De Cubber, G. (2017). Integrated data management for a fleet of search‐and‐rescue robots. Journal of Field Robotics, 34(3), 539-582.
  • [9] Bayindir, L., & Şahin, E. (2007). A review of studies in swarm robotics. Turkish Journal of Electrical Engineering & Computer Sciences, 15(2), 115-147.
  • [10] Gent, N., & Milton, R. (2018). Chemical, biological, radiological and nuclear incidents: clinical management and health protection. Publ Health Engl.
  • [11] Guchua, A. (2023). NATO’S ROLE IN THE POLICY OF NON-PROLIFERATION OF WEAPONS OF MASS DESTRUCTION AND GLOBAL SECURITY: A SHORT OVERVIEW. Journal of Liberty and International Affairs, 9(2), 495-506.
  • [12] Currie, J., & Heslop, D. (2018). Operational systems evaluation of a large scale multi-agency decontamination exercise. International Journal of Disaster Risk Reduction. https://doi.org/10.1016/J.IJDRR.2018.03.027.
  • [13] Kacer, P., Švrček, J., Syslová, K., Václavík, J., Pavlík, D., Červený, J., & Kuzma, M. (2012). Vapor Phase Hydrogen Peroxide – Method for Decontamination of Surfaces and Working Areas from Organic Pollutants. . https://doi.org/10.5772/33451.
  • [14] Lipp, M., Jaehnichen, G., Golecki, N., Fecht, G., Reichl, R., & Heeg, P. (2000). Microbiological, microstructure, and material science examinations of reprocessed Combitubes after multiple reuse.. Anesthesia and analgesia, 91 3, 693-7. https://doi.org/10.1097/00000539- 200009000-00037.
  • [15] Bayir, A., Eyi, Y., Durusu, M., Oztuna, A., & Eryilmaz, M. (2011). (P1-74) Introduction of the Portable Decontamination Unit of Gulhane Military Medical Academy. Prehospital and Disaster Medicine, 26, s122 - s123. https://doi.org/10.1017/S1049023X11004067.
  • [16] Rybka, A., Gavel, A., Pražák, P., Meloun, J., & Pejchal, J. (2019). Decontamination of CBRN units contaminated by highly contagious biological agents.. Epidemiologie, mikrobiologie, imunologie : casopis Spolecnosti pro epidemiologii a mikrobiologii Ceske lekarske spolecnosti J.E. Purkyne, 68 1, 40-45.
  • [17] Zhang, Y., Yan, K., Ji, F., & Zhang, L. (2018). Enhanced Removal of Toxic Heavy Metals Using Swarming Biohybrid Adsorbents. Advanced Functional Materials, 28. https://doi.org/10.1002/adfm.201806340.
  • [18] Xue, S. D., & Zeng, J. C. (2008). Control over swarm robots search with swarm intelligence principles. Journal of System Simulation, 20(13), 3449-3454.
  • [19] Wood, R. J., Nagpal, R., & Wei, G. Y. (2013). Flight of the RoboBees. Scientific American, 308(3), 60-65. https://doi.org/10.1038/scientificamerican0313-60
  • [20] Ma, K. Y., Chirarattananon, P., Fuller, S. B., & Wood, R. J. (2013). Controlled flight of a biologically inspired, insect-scale robot. Science, 340(6132), 603-607. https://doi.org/10.1126/science.1231806
  • [21] Hilder, J., Naylor, R., Rizihs, A., Franks, D., & Timmis, J. (2014). The Pi Swarm: A Low-Cost Platform for Swarm Robotics Research and Education. , 151-162. https://doi.org/10.1007/978-3-319-10401-0_14.
  • [22] Schranz, M., Umlauft, M., Sende, M., & Elmenreich, W. (2020). Swarm robotic behaviors and current applications. Frontiers in Robotics and AI, 7, 36. https://doi.org/10.3389/frobt.2020.00036
  • [23] Saska, M., Vonásek, V., Chudoba, J., Thomas, J., Loianno, G., & Kumar, V. (2016). Swarm distribution and deployment for cooperative surveillance by micro-aerial vehicles. Journal of Intelligent & Robotic Systems, 84, 469-492.
  • [24] Francesca, G., Brambilla, M., Brutschy, A., Garattoni, L., Miletitch, R., Podevijn, G., ... & Birattari, M. (2015). AutoMoDe-Chocolate: automatic design of control software for robot swarms. Swarm Intelligence, 9, 125-152.
  • [25] Kuckling, J., Van Pelt, V., & Birattari, M. (2022). AutoMoDe-Cedrata: automatic design of behavior trees for controlling a swarm of robots with communication capabilities. SN Computer Science, 3(2), 136.
  • [26] Shan, Q., & Mostaghim, S. (2020, October). Collective decision making in swarm robotics with distributed Bayesian hypothesis testing. In International Conference on Swarm Intelligence (pp. 55-67). Cham: Springer International Publishing.
  • [27] De Masi, G., & Ferrante, E. (2020, February). Quality-dependent adaptation in a swarm of drones for environmental monitoring. In 2020 Advances in Science and Engineering Technology International Conferences (ASET) (pp. 1-6). IEEE.
  • [28] Cambier, N., Albani, D., Frémont, V., Trianni, V., & Ferrante, E. (2021). Cultural evolution of probabilistic aggregation in synthetic swarms. Applied Soft Computing, 113, 108010.
  • [29] Wörn, H., Szymanski, M., & Seyfried, J. (2006). The I-SWARM project. ROMAN 2006 - The 15th IEEE International Symposium on Robot and Human Interactive Communication, 492-496. https://doi.org/10.1109/ROMAN.2006.314376.
  • [30] Li, M. (2019). Swarm Robot Task Planning Based on Air and Ground Coordination for Disaster Search and Rescue. Journal of Mechanical Engineering. https://doi.org/10.3901/jme.2019.11.001.
  • [31] Cardona, G., & Calderón, J. (2019). Robot Swarm Navigation and Victim Detection Using Rendezvous Consensus in Search and Rescue Operations. Applied Sciences. https://doi.org/10.3390/APP9081702.
  • [32] Song, Y., Liang, W., & Yang, Y. (2012). A method for grinding removal control of a robot belt grinding system. Journal of Intelligent Manufacturing, 23, 1903-1913. https://doi.org/10.1007/S10845-011-0508-6.
  • [33] Hilder, J., Naylor, R., Rizihs, A., Franks, D., & Timmis, J. (2014). The Pi Swarm: A Low-Cost Platform for Swarm Robotics Research and Education. , 151-162. https://doi.org/10.1007/978-3-319-10401-0_14.
  • [34] Duarte, M., Gomes, J., Costa, V., Rodrigues, T., Silva, F., Lobo, V., Marques, M., Oliveira, S., & Christensen, A. (2016). Application of swarm robotics systems to marine environmental monitoring. OCEANS 2016 - Shanghai, 1-8. https://doi.org/10.1109/OCEANSAP.2016.7485429.
  • [35] McGuire, K., Wagter, C., Tuyls, K., Kappen, H., & Croon, G. (2019). Minimal navigation solution for a swarm of tiny flying robots to explore an unknown environment. Science Robotics, 4. https://doi.org/10.1126/scirobotics.aaw9710.
  • [36] Ducatelle, F., Caro, G., Förster, A., Bonani, M., Dorigo, M., Magnenat, S., Mondada, F., O'Grady, R., Pinciroli, C., Rétornaz, P., Trianni, V., & Gambardella, L. (2014). Cooperative navigation in robotic swarms. Swarm Intelligence, 8, 1-33. https://doi.org/10.1007/s11721- 013-0089-4.
  • [37] Zhang, X., & Ali, M. (2020). A Bean Optimization-Based Cooperation Method for Target Searching by Swarm UAVs in Unknown Environments. IEEE Access, 8, 43850-43862. https://doi.org/10.1109/ACCESS.2020.2977499.
  • [38] Arvin, F., Murray, J., Shi, L., Zhang, C., & Yue, S. (2014). Development of an autonomous micro robot for swarm robotics. 2014 IEEE International Conference on Mechatronics and Automation, 635-640. https://doi.org/10.1109/ICMA.2014.6885771.
  • [39] Lee, W., & Kim, D. (2019). Adaptive approach to regulate task distribution in swarm robotic systems. Swarm Evol. Comput., 44, 1108- 1118. https://doi.org/10.1016/j.swevo.2018.11.005.
  • [40] Higgins, F., Tomlinson, A., & Martin, K. (2009). Survey on Security Challenges for Swarm Robotics. 2009 Fifth International Conference on Autonomic and Autonomous Systems, 307-312. https://doi.org/10.1109/ICAS.2009.62.
  • [41] Rango, F., Palmieri, N., Yang, X., & Marano, S. (2018). Swarm robotics in wireless distributed protocol design for coordinating robots involved in cooperative tasks. Soft Computing, 22, 4251-4266. https://doi.org/10.1007/s00500-017-2819-9.
  • [42] St-Onge, D., Kaufmann, M., Panerati, J., Ramtoula, B., Cao, Y., Coffey, E., & Beltrame, G. (2020). Planetary Exploration With Robot Teams: Implementing Higher Autonomy With Swarm Intelligence. IEEE Robotics & Automation Magazine, 27, 159-168. https://doi.org/10.1109/MRA.2019.2940413.
  • [43] Johnson, M., & Brown, D. (2016). Evolving and Controlling Perimeter, Rendezvous, and Foraging Behaviors in a Computation-Free Robot Swarm. EAI Endorsed Trans. Collab. Comput., 2, e5. https://doi.org/10.4108/eai.3-12-2015.2262390.
There are 43 citations in total.

Details

Primary Language English
Subjects Intelligent Robotics, Artificial Intelligence (Other)
Journal Section Reviews
Authors

Atakan Konukbay This is me 0000-0003-2404-0253

Ahmet Koluman 0000-0001-5308-8884

Publication Date December 24, 2023
Published in Issue Year 2023 Volume: 4 Issue: 2

Cite

APA Konukbay, A., & Koluman, A. (2023). Swarm Robots in CBRN Decontamination: Enhancing Efficiency and Safety. Journal of Smart Systems Research, 4(2), 72-81. https://doi.org/10.58769/joinssr.1362574
AMA Konukbay A, Koluman A. Swarm Robots in CBRN Decontamination: Enhancing Efficiency and Safety. JoinSSR. December 2023;4(2):72-81. doi:10.58769/joinssr.1362574
Chicago Konukbay, Atakan, and Ahmet Koluman. “Swarm Robots in CBRN Decontamination: Enhancing Efficiency and Safety”. Journal of Smart Systems Research 4, no. 2 (December 2023): 72-81. https://doi.org/10.58769/joinssr.1362574.
EndNote Konukbay A, Koluman A (December 1, 2023) Swarm Robots in CBRN Decontamination: Enhancing Efficiency and Safety. Journal of Smart Systems Research 4 2 72–81.
IEEE A. Konukbay and A. Koluman, “Swarm Robots in CBRN Decontamination: Enhancing Efficiency and Safety”, JoinSSR, vol. 4, no. 2, pp. 72–81, 2023, doi: 10.58769/joinssr.1362574.
ISNAD Konukbay, Atakan - Koluman, Ahmet. “Swarm Robots in CBRN Decontamination: Enhancing Efficiency and Safety”. Journal of Smart Systems Research 4/2 (December 2023), 72-81. https://doi.org/10.58769/joinssr.1362574.
JAMA Konukbay A, Koluman A. Swarm Robots in CBRN Decontamination: Enhancing Efficiency and Safety. JoinSSR. 2023;4:72–81.
MLA Konukbay, Atakan and Ahmet Koluman. “Swarm Robots in CBRN Decontamination: Enhancing Efficiency and Safety”. Journal of Smart Systems Research, vol. 4, no. 2, 2023, pp. 72-81, doi:10.58769/joinssr.1362574.
Vancouver Konukbay A, Koluman A. Swarm Robots in CBRN Decontamination: Enhancing Efficiency and Safety. JoinSSR. 2023;4(2):72-81.