Abstract
Swarm robotics is a decentralised mechanism used to coordinate a large group of simple robots. An exploration task means fully scanning an unknown area using a large number of robotic swarms. It has great potential for use in many real-world applications, such as monitoring extreme environments. Although there are many research studies on swarm exploration, the real-world scenarios of the swarm algorithm have not been fully investigated. This paper proposes a new application scenario for swarm exploration to monitor nuclear waste storage facilities. To coordinate the robotic swarm, the active elastic sheet model was utilised, which is a bio-inspired collective motion mechanism. We implemented the exploration scenario in a wet storage facility using a swarm of low-cost autonomous micro-surface robots, Bubbles. We developed a realistic kinematic model of the Bubble platform and implemented the exploration scenario using large swarm sizes. This paper showed the feasibility of using a low-cost robotic platform for this new application, although the accuracy of the path planning was not very high.
This work was supported in part by EPSRC RAIN and RNE projects [EP/R026084/1 and EP/P01366X/1].
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Pepper, S., Farnitano, M., Carelli, J., Hazeltine, J., Bailey, D.: Lessons learned in testing of safeguards equipment. Brookhaven National Lab. Upton, NY (US), Technical report (2001)
Doyle, J.: Nuclear Safeguards, Security and Nonproliferation: Achieving Security with Technology and Policy. Elsevier (2011)
Cheah, W., Groves, K., Martin, H., Peel, H., Watson, S., Marjanovic, O., Lennox, B.: Mirrax: a reconfigurable robot for limited access environments arXiv preprint arXiv:2203.00337 (2022)
West, C., et al.: A debris clearance robot for extreme environments. In: Althoefer, K., Konstantinova, J., Zhang, K. (eds.) TAROS 2019. LNCS (LNAI), vol. 11649, pp. 148–159. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-23807-0_13
Griffiths, A., Dikarev, A., Green, P.R., Lennox, B., Poteau, X., Watson, S.: AVEXIS-Aqua vehicle explorer for in-situ sensing. IEEE Robot. Autom. Lett. 1(1), 282–287 (2016)
Nancekievill, M., et al.: Development of a radiological characterization submersible ROV for use at fukushima daiichi. IEEE Trans. Nucl. Sci. 65(9), 2565–2572 (2018)
Lennox, C., Groves, K., Hondru, V., Arvin, F., Gornicki, K., Lennox, B.: Embodiment of an aquatic surface vehicle in an omnidirectional ground robot. In: 2019 IEEE International Conference on Mechatronics (ICM), vol. 1, pp. 182–186. IEEE (2019)
Groves, K., West, A., Gornicki, K., Watson, S., Carrasco, J., Lennox, B.: Mallard: an autonomous aquatic surface vehicle for inspection and monitoring of wet nuclear storage facilities. Robotics 8(2), 47 (2019)
Dorigo, M., Theraulaz, G., Trianni, V.: Reflections on the future of swarm robotics. Sci. Robot. 5(49), eabe4385 (2020)
Schranz, M., et al.: Swarm intelligence and cyber-physical systems: concepts, challenges and future trends. Swarm Evol. Comput. 60, 100762 (2021)
Schmickl, T., et al.: Get in touch: cooperative decision making based on robot-to-robot collisions. Autonom. Agents Multi-Agent Syst. 18(1), 133–155 (2009)
Ferrante, E., Turgut, A.E., Dorigo, M., Huepe, C.: Collective motion dynamics of active solids and active crystals. New J. Phys. 15(9), 095011 (2013)
Raoufi, M., Turgut, A.E., Arvin, F.: Self-organized collective motion with a simulated real robot swarm. In: Althoefer, K., Konstantinova, J., Zhang, K. (eds.) TAROS 2019. LNCS (LNAI), vol. 11649, pp. 263–274. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-23807-0_22
Liang, X., Qu, X., Hou, Y., Li, Y., Zhang, R.: Distributed coordinated tracking control of multiple unmanned surface vehicles under complex marine environments. Ocean Eng. 205, 107328 (2020)
Huang, B., Song, S., Zhu, C., Li, J., Zhou, B.: Finite-time distributed formation control for multiple unmanned surface vehicles with input saturation. Ocean Eng. 233, 109158 (2021)
Liu, Y., Song, R., Bucknall, R., Zhang, X.: Intelligent multi-task allocation and planning for multiple unmanned surface vehicles (USVS) using self-organising maps and fast marching method. Inf. Sci. 496, 180–197 (2019)
Davey, A.: The growth of Taylor vortices in flow between rotating cylinders. J. Fluid Mech. 14(3), 336–368 (1962)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
He, Y., Lennox, B., Arvin, F. (2022). Exploration of Underwater Storage Facilities with Swarm of Micro-surface Robots. In: Pacheco-Gutierrez, S., Cryer, A., Caliskanelli, I., Tugal, H., Skilton, R. (eds) Towards Autonomous Robotic Systems. TAROS 2022. Lecture Notes in Computer Science(), vol 13546. Springer, Cham. https://doi.org/10.1007/978-3-031-15908-4_8
Download citation
DOI: https://doi.org/10.1007/978-3-031-15908-4_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-15907-7
Online ISBN: 978-3-031-15908-4
eBook Packages: Computer ScienceComputer Science (R0)