Abstract
Understanding how multiple drones can coordinate and communicate is essential for advancing multi-agent robotics. Multiple drone applications are growing with technology and have reached areas such as: farming, meteorology, pollution detection, and forest fire monitoring. The focus of this paper is to illustrate how current systems manage mission control and communication strategies for multi-agent drone deployments. The primary scope was to examine papers that provide promising experimental results and analyze popular communication hardware used. Principal results included the classification of two main mission control strategies: centralized and decentralized. In addition the two most popular formation strategies leader-follower and virtual structure were compared. Finally, successful experimental frameworks that were used for practical applications were introduced and classified. Most results were limited in number of agents or were in their initial experimental stages. The literature review revealed a need for a greater focus on overall robustness of multi-agent systems.
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Cho, A., Kim, J., Lee, S., Kee, C.: Wind estimation and airspeed calibration using a UAV with a single antenna GPS receiver and pitot tube. IEEE Trans. Aerosp. Electron. Syst. 47(1), 109–117 (2011)
Caltabiano, D., Muscato, G., Orlando, A., Federico, C, Giudice, G., Guerrieri, S.: Architecture of a UAV for volcanic gas sampling. IEEE Conference on Emerging Technologies and Factory Auto- mation 1, 739–744 (2005)
McGonigle, A.J.S., Aiuppa, A., Giudice, G., Tamburello, G., Hodson, A.J., Gurrieri, G.: Unmanned aerial vehicle measurements of volcanic carbon dioxide fluxes. Geophyshical Res. Lett. 35(6), 1–4 (2008)
Van den Kroonenberg, A., Martin, T., Buschmann, M., Bange, J., Vörsmann, P.: Measuring the wind vector using the autonomous mini aerial vehicle M 2 AV. J. Atmos. Ocean. Technol. 25(11), 1969–1982 (2008)
Faical, B.S., Costa, F.G., Pessin, G., Ueyama, J., Freitas, H., Colombo, A., Fini, P.H., Villas, L., Osorio, F.S., Vargas, P.A., Braun, T.: The use of unmanned aerial vehicles and wireless sensor networks for spraying pesticides. J. Syst. Archit. 60(4), 393–404 (2014)
Logan, M.J. et al.: Small UAV research and evolution in long endurance electric powered vehicles. In: American Institute of Aeronautics and Astronautics Conference and Exhibit, pp 1–7, Rohnert Park (2007)
Beni, G.: From swarm intelligence to swarm robotics. Swarm Robotics. Springer, Berlin (2005). Online ISBN:978-3-540-30552-1
Quaritsch, M., et al.: Collaborative microdrones: applications and research challenges. In: of The 2nd International Conference on Autonomic Computing and CommunicationSystems, Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, Turin (2008)
Purta, R., Nagrecha, S., Madey, G.: Multi-hop Communications in a Swarm of UAVs. In: Agent-Directed Simulation SymposiumSociety for Computer Simulation International, San Diego (2013)
Yuta, S., Premvuti, S.: Coordinating autonomous and centralized decision making to achieve cooperative behaviors between multiple mobile robots. In: Intelligent Robots and Systems, lEEE/RSJ International Conference, vol. 3, Raleigh (1992)
McLain, T.W., et al.: Cooperative control of UAV rendezvous. In: American Control Conference, vol. 3, Arlington (2001)
Acevedo, J.J. et al.: Decentralized strategy to ensure information propagation in area monitoring missions with a team of UAVs under limited communications. In: Unmanned Aircraft Systems (ICUAS), Grand Hyatt (2013)
Acevedo, J.J. et al.: One-to-one coordination algorithm for decentralized area partition in surveillance missions with a team of aerial robots. J. Intell. Robot. Syst. 74, 269–285 (2014)
Saha, M., Pekka, I.: Multi-robot motion planning by incremental coordination. In: IEEE/RSJ International Conference Intelligent Robots and Systems (2006)
Kazanzides, P., Thienphrapa, P.: Centralized processing and distributed I/O for robot control. In: IEEE International Conference Technologies for Practical Robot Applications (2008)
Weiss, N., Norbert, J.: Towards local vision in centralized robot soccer leagues: A robust and flexible vision system also allowing varying degrees of robot autonomy. In: Proceedings of the FIRA World Congress (2004)
Borrelli, F., et al.: Collision-free UAV formation flight using decentralized optimization and invariant sets. In: Decision and Control IEEE Conference on, vol. 1 (2004)
Tanner, H., Christodoulakis, D.: Decentralized cooperative control of heterogeneous vehicle groups. Robot. Auton. Syst. 11, 811–823 (2007)
Clare, A., Cummings, M.: Task-based interfaces for decentralized multiple unmanned vehicle control. In: Proceedings of AUVSI (2011)
Chen, X., Serrani, A., Ozbay, H.: Control of leader-follower formations of terrestrial UAVs. In: 42nd IEEE Conference Decision and Control, vol. 1 (2003)
Shao, J. et al.: Leader-following formation control of multiple mobile robots. In: Intelligent Control, IEEE International Symposium on, Mediterrean Conference on Control and Automation, Limassol (2005)
Standard: IEEE 802.11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications. (2012 revision). https://doi.org/10.1109/IEEESTD.2012.6178212. Accessed 5 April 2012
Standard: IEEE 802.15.4: Low-Rate Wireless Personal Area Networks 16 (2011)
Tan, K.N., Lewis, M.: Virtual structures for high-precision cooperative mobile robotic control. In: Intelligent Robots and Systems, IEEE/RSJ, vol. 1, Osaka (1996)
Askari, A., et al.: UAV formation control via the virtual structure approach. J. Aerosp. Eng. 28(1), 04014047 (2013)
Wang, J. et al.: Robustness analysis of leader-follower consensus. J. Syst. Sci. Complex. 22(2), 186–206 (2009)
Hogg, R. et al.: Sensors and algorithms for small robot leader/follower behavior. In: Aerospace/Defense Sensing, Simulation, and Controls. International Society for Optics and Photonics (2001)
Mariottini, G. et al.: Leader-follower formations: Uncalibrated vision-based localization and control. In: IEEE International Conference on Robotics and Automation (2007)
Ren, W., Beard, R.: Decentralized scheme for spacecraft formation flying via the virtual structure approach. J. Guid. Control Dyn. 27(1), 73–82 (2004)
Low, C., Quee, N.: A flexible virtual structure formation keeping control for fixed-wing UAVs. In: 9th IEEE International Conference on Control and Automation (ICCA) (2011)
Kowalczyk, W.: Multi-robot coordination. In: Proceedings of the Second International Workshop on Robot Motion and Control (2001)
Bürkle, A., Segor, F., Kollmann, M.: Towards Autonomous Micro UAV Swarms. J. Intell. Robot. Syst. 61(1), 339–353 (2011)
Leuchter, S., Partmann, T., Berger, L., Blum, E.J., Schönbein, R.: Karlsruhe generic agile ground station. In: Beyerer, J. (ed.) Future Security. 2nd Security Research Conference, Fraunhofer Defense and Security Alliance, pp 159–162, Karlsruhe (2007)
Kushleyev, A., Mellinger, D., Powers, C., Kumar, V.: Towards a swarm of agile micro quadrotors. Auton. Robot. 35(4), 287–300 (2013)
Vicon Motion Camera http://www.vicon.com/products/camera-systems Accessed 8 June 2015
MATLAB http://www.mathworks.com/products/matlab/ Accessed 8 June 2015
Dantu, K., et al.: Programming micro-aerial vehicle swarms with karma. In: The 9th ACM Conference on Embedded Networked Sensor Systems, Seattle (2011)
Jbullet http://jbullet.advel.cz/ Accessed 8 June 2015
Simbeeotic https://github.com/bryankate/simbeeotic/wiki Accessed 8 June 2015
mCX2 http://www.bladehelis.com/Products/Default.aspx?ProdID(=)EFLH2400 Accessed 8 June 2015
900 MHz Modem http://www.digi.com/products/wireless-modems-peripherals/wireless-range-extenders-peripherals/xtend Accessed 8 June 2015
Chao, H., Baumann, M., Jensen, A., Chen, Y., Cao, Y., Ren, W., McKee, M.: Band-reconfigurable multi-UAV-based cooperative remote sensing for real-time water management and distributed irrigation control. In: IFAC World Congress, Seoul (2008)
CR206 Datalogger https://www.campbellsci.ca/cr206 Accessed 8 June 2015
Schmickl, T. et al.: CoCoRo–The Self-Aware Underwater Swarm. In: 2011 Fifth IEEE Conference Self-Adaptive and Self-Organizing Systems Workshops (SASOW), Ann Arbor (2011)
Akyildiz, I.F., Pompili, D., Melodia, T.: Challenges for efficient communication in underwater acoustic sensor networks. ACM SIGBED Review, Special issue on embedded sensor networks and wireless computing. 1(2), 3–8 (2004)
Yun, B., Chen, B.M., Lum, K.Y., Lee, T.H.: Design and implementation of a leader-follower cooperative control system for unmanned helicopters. J. Control Theory Appl. 8(1), 61–68 (2010)
Freewave Modem http://www.freewave.com/products.aspx Accessed 8 June 2015
Avan den Broek, T., Huijberts, H., van de Wouw, N., Kostic, D., Nijmeijer, H.: A virtual structure approach to formation control of unicycle mobile robots using mutual coupling. Int. J. Control 84(11), 1886–1902 (2011)
E-puck Robots http://www.e-puck.org/ Accessed June 8 2015
Li, N., Liu, H.: Multiple UAVs Formation Flight Experiments Using Virtual Structure and Motion Synchronization. In: The AIAA Guidance, Navigation, and Control Conference, Chicago (2009)
Gumstix Computers https://www.gumstix.com/ Accessed 8 2015
Osterloh, C., Thilo, P., Erik, M.: MONSUN II: A small and inexpensive AUV for underwater swarms. In: Robotics; ROBOTIK 2012, 7th German Conference on VDE, Munich (2012)
BeagleBone http://beagleboard.org/ Accessed 8 June 2015
Varela, G., Caamamo, P., Orjales, F., Deibe, A., López-Peña, F., Duro, R.J.: Swarm intelligence based approach for real time UAV team coordination in search operations. In: Nature and Biologically Inspired Computing (NaBIC), Mexico (2011)
Olivieri, B., Endler, M.: An ubiquitous based approach for Movement Coordination of Swarms of Unmanned Aerial Vehicles using mobile networks. In: VI SimposioBrasileiro de ComputaçãoUbiqua e Pervasiva (2014)
David, L., Vasconcelos, R., Alves, L., André, R., Endler, M.: A DDS-based middleware for scalable tracking, communication and collaboration of mobile nodes. J. Internet Serv. Appl. 4(1), 1–15 (2013)
Costa, F.G. et al.: The use of unmanned aerial vehicles and wireless sensor network in agricultural applications. In: Geoscience and Remote Sensing Symposium (IGARSS), Munich (2012)
XBEE Pro Series http://www.digi.com/products/wireless-wired-embedded-solutions/zigbee-rf-modules/zigbee-mesh-module/xbee-zb-module Accessed 8 June 2015
standard, E I A: RS-232-C: Interface between Data Terminal Equipment and Data Communication Equipment Employing Serial Binary Data Interchange. Electronic Industries Association Engineering Dept, Washington (1969)
Lee, J.-S., Su, Y.-W., Shen, C.-C.: A Comparative Study of Wireless Protocols: Bluetooth, UWB, ZigBee, and Wi-Fi. In: The 33rd Annual Conference of the IEEE Industrial Electronics Society (IECON), Taipei (2007)
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Pantelimon, G., Tepe, K., Carriveau, R. et al. Survey of Multi-agent Communication Strategies for Information Exchange and Mission Control of Drone Deployments. J Intell Robot Syst 95, 779–788 (2019). https://doi.org/10.1007/s10846-018-0812-x
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DOI: https://doi.org/10.1007/s10846-018-0812-x