Abstract
In this paper, we introduce a distributed autonomous flocking behavior of Unmanned Aerial Vehicles (UAVs) in demanding outdoor conditions, motivated by search and rescue applications. We propose a novel approach for decentralized swarm navigation in the direction of a candidate object of interest (OOI) based on real-time detections from onboard RGB cameras. A novel self-adaptive communication strategy secures an efficient change of swarm azimuth to a higher priority direction based on the real-time detections. We introduce a local visual communication channel that establishes a network connection between neighboring robots without explicit communication to achieve high reliability and scalability of the system. As a case study, this novel method is applied for the deployment of a UAV swarm towards detected OOI for closer inspection and verification. The results of simulations and real-world experiments have verified the intended behavior of the swarm system for the detection of true positive and false positive OOI, as well as for cooperative environment exploration.
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References
Ahmad, A., Walter, V., Petracek, P., Petrlik, M., Baca, T., Zaitlik, D., & Saska, M. (2021). Autonomous aerial swarming in GNSS-denied environments with high obstacle density. In IEEE ICRA. https://doi.org/10.1109/ICRA48506.2021.9561284
Akat, SB., & Gazi, V. (2008). Particle swarm optimization with dynamic neighborhood topology: Three neighborhood strategies and preliminary results. In IEEE swarm intelligence symposium. https://doi.org/10.1109/SIS.2008.4668298
Araujo, F., Santos, J., & Rocha, R. P. (2014). Implementation of a routing protocol for ad hoc networks in search and rescue robotics. In IFIP WD. https://doi.org/10.1109/WD.2014.7020821
Arnold, R. D., Yamaguchi, H., & Tanaka, T. (2018). Search and rescue with autonomous flying robots through behavior-based cooperative intelligence. Journal of International Humanitarian Action, 3(1), 1–18. https://doi.org/10.1186/s41018-018-0045-4.
Baca, T., Hert, D., Loianno, G., Saska, M., & Kumar, V. (2018). Model predictive trajectory tracking and collision avoidance for reliable outdoor deployment of unmanned aerial vehicles. In 2018 IEEE/RSJ international conference on intelligent robots and systems, IEEE (pp 1–8). https://doi.org/10.1109/IROS.2018.8594266
Baca, T., Petrlik, M., Vrba, M., Spurny, V., Penicka, R., Hert, D., & Saska, M. (2021). The MRS UAV system: Pushing the frontiers of reproducible research, real-world deployment, and education with autonomous unmanned aerial vehicles. Journal of Intelligent & Robotic Systems, 102(26), 1–28. https://doi.org/10.1007/s10846-021-01383-5.
Cardona, G. A., & Calderon, J. M. (2019). Robot swarm navigation and victim detection using rendezvous consensus in search and rescue operations. Applied Sciences, 9(8), 1702. https://doi.org/10.3390/app9081702.
Cardona, G. A., Yanguas-Rojas, D., Arevalo-Castiblanco, M. F., & Mojica-Nava, E. (2019). Ant-based multi-robot exploration in non-convex space without global-connectivity constraints. In ECC. https://doi.org/10.23919/ECC.2019.8796034
Carpentiero, M., Gugliermetti, L., Sabatini, M., & Palmerini, G. B. (2017). A swarm of wheeled and aerial robots for environmental monitoring. In IEEE ICNSC. https://doi.org/10.1109/ICNSC.2017.8000073
Chen, X., Tang, J., & Lao, S. (2020). Review of unmanned aerial vehicle swarm communication architectures and routing protocols. Applied Sciences, 10(10), 3661. https://doi.org/10.3390/app10103661.
Cheng, L., Viriyasitavat, W., Boban, M., & Tsai, H. M. (2017). Comparison of radio frequency and visible light propagation channels for vehicular communications. IEEE Access, 6, 2634–2644.
Chowdhury, M. Z., Hossan, M. T., Islam, A., & Jang, Y. M. (2018). A comparative survey of optical wireless technologies: Architectures and applications. IEEE Access, 6, 9819–9840.
Chung, S. J., Paranjape, A. A., Dames, P., Shen, S., & Kumar, V. (2018). A survey on aerial swarm robotics. IEEE Transactions on Robotics, 34(4), 837–855. https://doi.org/10.1109/TRO.2018.2857475.
Couceiro, MS., Portugal, D., & Rocha, R. P. (2013). A collective robotic architecture in search and rescue scenarios. In ACM symposium on applied computing, https://doi.org/10.1145/2480362.2480377
De Benedetti, M., D’Urso, F., Fortino, G., Messina, F., Pappalardo, G., & Santoro, C. (2017). A fault-tolerant self-organizing flocking approach for UAV aerial survey. Journal of Network and Computer Applications, 96, 14–30. https://doi.org/10.1016/j.jnca.2017.08.004.
Eudes, A., Marzat, J., Sanfourche, M., Moras, J., & Bertrand, S. (2018). Autonomous and safe inspection of an industrial warehouse by a multi-rotor MAV. In FSR. https://doi.org/10.1007/978-3-319-67361-5_15
Ferrante, E., Turgut, A. E., Huepe, C., Stranieri, A., Pinciroli, C., & Dorigo, M. (2012). Self-organized flocking with a mobile robot swarm: a novel motion control method. Adaptive Behavior, 20(6), 460–477. https://doi.org/10.1177/1059712312462248.
Ferrante, E., Turgut, A. E., Stranieri, A., Pinciroli, C., Birattari, M., & Dorigo, M. (2014). A self-adaptive communication strategy for flocking in stationary and non-stationary environments. Natural Computing, 13(2), 225–245. https://doi.org/10.1007/s11047-013-9390-9.
Gazi, V., & Passino, K. (2002). A class of attraction/repulsion functions for stable swarm aggregations. In IEEE CDC. https://doi.org/10.1080/00207170412331330021
Hayat, S., Yanmaz, E., Bettstetter, C., & Brown, T. X. (2020). Multi-objective drone path planning for search and rescue with quality-of-service requirements. Autonomous Robots, 44(7), 1183–1198. https://doi.org/10.1007/s10514-020-09926-9.
Hornischer, H., Varughese, J. C., Thenius, R., Wotawa, F., Füllsack, M., & Schmickl, T. (2021). CIMAX: Collective information maximization in robotic swarms using local communication. Adaptive Behavior, 29(3), 297–314. https://doi.org/10.1177/1059712320912021.
Horyna, J., Walter, V., & Saska, M. (2022). UVDAR-COM: UV-based relative localization of UAVs with integrated optical communication. In ICUAS
Intel Corporation. (2018). Openvino toolkit documentation. https://docs.openvinotoolkit.org/latest/index.html
Kaushal, H., & Kaddoum, G. (2016). Optical communication in space: Challenges and mitigation techniques. IEEE Communications Surveys & Tutorials, 19(1), 57–96. https://doi.org/10.1109/COMST.2016.2603518.
Khalighi, M. A., & Uysal, M. (2014). Survey on free space optical communication: A communication theory perspective. IEEE Communications Surveys & Tutorials, 16(4), 2231–2258. https://doi.org/10.1109/COMST.2014.2329501.
Krishnanand, K., & Ghose, D. (2009). Glowworm swarm optimization for simultaneous capture of multiple local optima of multimodal functions. Swarm Intelligence, 3(2), 87–124. https://doi.org/10.1007/s11721-008-0021-5.
Madridano, Á., Al-Kaff, A., Flores, P., Martín, D., & de la Escalera, A. (2021). Software architecture for autonomous and coordinated navigation of UAV swarms in forest and urban firefighting. Applied Sciences, 11(3), 1258. https://doi.org/10.3390/app11031258.
Merheb, A. R., Gazi, V., & Sezer-Uzol, N. (2016). Implementation studies of robot swarm navigation using potential functions and panel methods. IEEE/ASME Transactions on Mechatronics, 21(5), 2556–2567. https://doi.org/10.1109/TMECH.2016.2580303.
Miiller, M., Steidle, F., Schuster, MJ., Lutz, P., Maier, M., Stoneman, S., Tomic, T., & Stürzl, W. (2018). Robust visual-inertial state estimation with multiple odometries and efficient mapping on an MAV with ultra-wide FOV stereo vision. In IEEE/RSJ IROS. https://doi.org/10.1109/IROS.2018.8594117
Nascimento, T. P., Moreira, A. P., Conceição, A. G. S., & Bonarini, A. (2013). Intelligent state changing applied to multi-robot systems. Robotics and Autonomous Systems, 61(2), 115–124. https://doi.org/10.1016/j.robot.2012.10.011.
Petracek, P., Walter, V., Baca, T., & Saska, M. (2020). Bio-inspired compact swarms of unmanned aerial vehicles without communication and external localization. Bioinspiration & Biomimetics, 16(2), 026009.
Saska, M., Baca, T., Thomas, J., Chudoba, J., Preucil, L., Krajnik, T., et al. (2017). System for deployment of groups of unmanned micro aerial vehicles in GPS-denied environments using onboard visual relative localization. Autonomous Robots, 41(4), 919–944. https://doi.org/10.1007/s10514-016-9567-z.
Stasinchuk, Y., Vrba, M., Petrlik, M., Baca, T., Spurny, V., Hert, D., Zaitlik, D., Nascimento, T., & Saska, M. (2021). A multi-UAV system for detection and elimination of multiple targets. In IEEE ICRA. https://doi.org/10.1109/ICRA48506.2021.9562057
Varughese, J. C., Hornischer, H., Zahadat, P., Thenius, R., Wotawa, F., & Schmickl, T. (2020). A swarm design paradigm unifying swarm behaviors using minimalistic communication. Bioinspiration & biomimetics, 15(3), 1–27.
Walter, V., Saska, M., & Franchi, A. (2018a). Fast mutual relative localization of UAVs using ultraviolet led markers. In ICUAS. https://doi.org/10.1109/ICUAS.2018.8453331
Walter, V., Staub, N., Saska, M., & Franchi, A. (2018b). Mutual localization of UAVs based on blinking ultraviolet markers and 3D time-position hough transform. In IEEE CASE. https://doi.org/10.1109/COASE.2018.8560384
Walter, V., Staub, N., Franchi, A., & Saska, M. (2019). UVDAR system for visual relative localization with application to leader-follower formations of multirotor UAVs. IEEE Robotics and Automation Letters, 4(3), 2637–2644. https://doi.org/10.1109/LRA.2019.2901683.
Wiltsche, C., Lygeros, J., & Ramponi, F. A. (2013). Synthesis of an asynchronous communication protocol for search and rescue robots. In IEEE ECC. https://doi.org/10.23919/ECC.2013.6669133
Yoshimoto, M., Endo, T., Maeda, R., & Matsuno, F. (2018). Decentralized navigation method for a robotic swarm with nonhomogeneous abilities. Autonomous Robots, 42(8), 1583–1599. https://doi.org/10.1007/s10514-018-9774-x.
Zhao, H., Liu, H., Leung, Y. W., & Chu, X. (2018). Self-adaptive collective motion of swarm robots. IEEE Transactions on Automation Science and Engineering, 15(4), 1533–1545. https://doi.org/10.1109/TASE.2018.2840828.
Acknowledgements
This work was supported by the Technology Innovation Institute - Sole Proprietorship LLC, UAE, under the Research Project Contract No. TII/ATM/2032/2020, by CTU grant no SGS20/174/OHK3/3T/13, and by the Czech Science Foundation (GAČR) under research project No. 20-10280S.
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Horyna, J., Baca, T., Walter, V. et al. Decentralized swarms of unmanned aerial vehicles for search and rescue operations without explicit communication. Auton Robot 47, 77–93 (2023). https://doi.org/10.1007/s10514-022-10066-5
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DOI: https://doi.org/10.1007/s10514-022-10066-5