Abstract
This work focuses on an autonomous swarm of drones, a multi-agent system, where the leader agent has the capability of intelligent decision making while the other agents in the swarm follow the leader blindly. The proposed algorithm helps with cost cutting especially in the multi-drone systems, i.e., swarms, by reducing the power consumption and processing requirements of each individual agent. It is shown that by applying a pre-specified formation design with feedback cross-referencing between the agents, the swarm as a whole can not only maintain the desired formation and navigate but also avoid collisions with obstacles and other drones. Furthermore, the power consumed by the nodes in the considered test scenario, is reduced by 50% by utilising the proposed methodology.
This work has been supported in part by the Academy of Finland-funded research project 314048 and Finnish Cultural Foundation.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Campion, M., Ranganathan, P., Faruque, S.: A review and future directions of UAV swarm communication architectures. In: 2018 IEEE International Conference on Electro/Information Technology (EIT), pp. 0903–0908, May 2018
Murray, R.: Recent research in cooperative control of multi-vehicle systems. J. Dyn. Syst. Meas. Control 129, 571–598 (2007)
He, L., Bai, P., Liang, X., Zhang, J., Wang, W.: Feedback formation control of UAV swarm with multiple implicit leaders. Aerosp. Sci. Technol. 72, 327–334 (2018). https://doi.org/10.1016/j.ast.2017.11.020, http://www.sciencedirect.com/science/article/pii/S1270963816309816
Ladd, G., Bland, G.: Non-military applications for small UAS platforms. In: AIAA Infotech@ Aerospace Conference and AIAA Unmanned... Unlimited Conference, p. 2046 (2009)
Mualla, Y., et al.: Agent-based simulation of unmanned aerial vehicles in civilian applications: a systematic literature review and research directions. Future Gener. Comput. Syst. 100, 344–364 (2019). https://doi.org/10.1016/j.future.2019.04.051, http://www.sciencedirect.com/science/article/pii/S0167739X18328462
Gkiokas, A., Cristea, A.I.: Cognitive agents and machine learning by example: representation with conceptual graphs. Comput. Intell. 34(2), 603–634 (2018). https://doi.org/10.1111/coin.12167, https://onlinelibrary.wiley.com/doi/abs/10.1111/coin.12167
Dorri, A., Kanhere, S.S., Jurdak, R.: Multi-agent systems: a survey. IEEE Access 6, 28573–28593 (2018)
Zhuge, C., Cai, Y., Tang, Z.: A novel dynamic obstacle avoidance algorithm based on collision time histogram. Chin. J. Electron. 26(3), 522–529 (2017)
Wang, X., Yadav, V., Balakrishnan, S.N.: Cooperative uav formation flying with obstacle/collision avoidance. IEEE Trans. Control Syst. Technol. 15(4), 672–679 (2007)
Wei, R.: Consensus based formation control strategies for multi-vehicle systems. In: 2006 American Control Conference, pp. 6pp., June 2006
Low, C.B., Ng, Q.S.: A flexible virtual structure formation keeping control for fixed-wing UAVs. In: 2011 9th IEEE International Conference on Control and Automation (ICCA), pp. 621–626, December 2011
Beard, R.W., Lawton, J., Hadaegh, F.Y.: A coordination architecture for spacecraft formation control. IEEE Trans. Control Syst. Technol. 9(6), 777–790 (2001)
Li, N.H., Liu, H.H.: Formation UAV flight control using virtual structure and motion synchronization. In: 2008 American Control Conference, pp. 1782–1787. IEEE (2008)
Dong, L., Chen, Y., Qu, X.: Formation control strategy for nonholonomic intelligent vehicles based on virtual structure and consensus approach. Procedia Eng. 137, 415–424 (2016). Green Intelligent Transportation System and Safety
Oh, K.K., Park, M.C., Ahn, H.S.: A survey of multi-agent formation control. Automatica 53, 424–440 (2015)
Buzogany, L., Pachter, M., D’azzo, J.: Automated control of aircraft in formation flight. In: Guidance, Navigation and Control Conference, p. 3852 (1993)
Shen, D., Sun, Z., Sun, W.: Leader-follower formation control without leader’s velocity information. Sci. China Inf. Sci. 57(9), 1–12 (2014)
Han, Q., Li, T., Sun, S., Villarrubia, G., de la Prieta, F.: “1-N” leader-follower formation control of multiple agents based on bearing-only observation. In: Demazeau, Y., Decker, K.S., Bajo Pérez, J., de la Prieta, F. (eds.) Advances in Practical Applications of Agents, Multi-Agent Systems, and Sustainability: The PAAMS Collection, pp. 120–130. Springer International Publishing, Cham (2015). https://doi.org/10.1007/978-3-319-18944-4_10
Lawton, J.R., Beard, R.W., Young, B.J.: A decentralized approach to formation maneuvers. IEEE Trans. Robot. Autom. 19(6), 933–941 (2003)
Balch, T., Arkin, R.C.: Behavior-based formation control for multirobot teams. IEEE Trans. Robot. Autom. 14(6), 926–939 (1998)
Zhang, X., Liniger, A., Borrelli, F.: Optimization-based collision avoidance. arXiv preprint arXiv:1711.03449 (2017)
Pham, H., Smolka, S.A., Stoller, S.D., Phan, D., Yang, J.: A survey on unmanned aerial vehicle collision avoidance systems. CoRR abs/1508.07723 (2015). http://arxiv.org/abs/1508.07723
Smith, N.E., Cobb, R., Pierce, S.J., Raska, V.: Optimal collision avoidance trajectories via direct orthogonal collocation for unmanned/remotely piloted aircraft sense and avoid operations. In: AIAA Guidance, Navigation, and Control Conference, p. 0966 (2014)
Yasin, J.N., Haghbayan, M.H., Heikkonen, J., Tenhunnen, H., Plosila, J.: Formation maintenance and collision avoidance in a swarm of drones. In: Proceedings of the 3rd International Symposium on Computer Science and Intelligent Control. ISCSIC 2019, Amsterdam, Netherlands. ACM, September 2019
Prats, X., Delgado, L., Ramirez, J., Royo, P., Pastor, E.: Requirements, issues, and challenges for sense and avoid in unmanned aircraft systems. J. Aircr. 49(3), 677–687 (2012)
Albaker, B.M., Rahim, N.A.: A survey of collision avoidance approaches for unmanned aerial vehicles. In: 2009 International Conference for Technical Postgraduates (TECHPOS), pp. 1–7, December 2009. https://doi.org/10.1109/TECHPOS.2009.5412074
Soriano, A., Bernabeu, E.J., Valera, A., Vallés, M.: Multi-agent systems platform for mobile robots collision avoidance. In: Demazeau, Y., Ishida, T., Corchado, J.M., Bajo, J. (eds.) Advances on Practical Applications of Agents and Multi-Agent Systems, pp. 320–323. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-38073-0_37
Albaker, B.M., Rahim, N.A.: Unmanned aircraft collision detection and resolution: concept and survey. In: 2010 5th IEEE Conference on Industrial Electronics and Applications, pp. 248–253, June 2010. https://doi.org/10.1109/ICIEA.2010.5516808
Seo, J., Kim, Y., Kim, S., Tsourdos, A.: Collision avoidance strategies for unmanned aerial vehicles in formation flight. IEEE Trans. Aerosp. Electron. Syst. 53(6), 2718–2734 (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Yasin, J.N., Mohamed, S.A.S., Haghbayan, MH., Heikkonen, J., Tenhunen, H., Plosila, J. (2020). Navigation of Autonomous Swarm of Drones Using Translational Coordinates. In: Demazeau, Y., Holvoet, T., Corchado, J., Costantini, S. (eds) Advances in Practical Applications of Agents, Multi-Agent Systems, and Trustworthiness. The PAAMS Collection. PAAMS 2020. Lecture Notes in Computer Science(), vol 12092. Springer, Cham. https://doi.org/10.1007/978-3-030-49778-1_28
Download citation
DOI: https://doi.org/10.1007/978-3-030-49778-1_28
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-49777-4
Online ISBN: 978-3-030-49778-1
eBook Packages: Computer ScienceComputer Science (R0)