Abstract
The main goal of swarm robotics is to control a large number of robots that interact together without a central controller. Swarm systems have a broad range of application areas, including the exploration and monitoring of extreme environments. This paper proposes a new approach to the coordination of a leader-follower system for use by a swarm of surface robots that are focused on the exploration of an unknown environment. The leader robot is controlled semi-autonomously by receiving a trajectory from a user and the swarm followers are then coordinated by a bio-inspired collective motion adapted from the state-of-the-art model, Active Elastic Sheet. To implement the proposed swarm controller, an open-source simulation platform, Gazebo, was used where the leader and follower robots, as well as a pond containing water, were simulated. The results demonstrate the feasibility of using the proposed swarm system in exploration applications.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
References
Doyle, J.: Nuclear Safeguards, Security and Nonproliferation: Achieving Security with Technology and Policy. Elsevier (2011)
Pepper, S., Farnitano, M., Carelli, J., Hazeltine, J., Bailey, D.: Lessons Learned in Testing of Safeguards Equipment. Brookhaven National Lab., Upton, NY (US), Tech. Rep. (2001)
Huang, X., Arvin, F., West, C., Watson, S., Lennox, B.: Exploration in extreme environments with swarm robotic system. In: IEEE international conference on Mechatronics (ICM), vol. 1, pp. 193–198. IEEE (2019)
Hu, J., Niu, H., Carrasco, J., Lennox, B., Arvin, F.: Voronoi-based multi-robot autonomous exploration in unknown environments via deep reinforcement learning. IEEE Trans. Vehicul. Technol. 69(12), 14413–14423 (2020)
Green, T., et al.: A minimalist solution to the multi-robot barrier coverage problem. In: Fox, C., et al. (eds.) TAROS 2021. LNCS (LNAI), vol. 13054, pp. 349–353. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-89177-0_35
Hu, J., Lennox, B., Arvin, F.: Collaborative coverage for a network of vacuum cleaner robots. In: Annual Conference Towards Autonomous Robotic Systems, pp. 112–115 (2021)
Turgut, A.E., Çelikkanat, H., Gökçe, F., Şahin, E.: Self-organized flocking in mobile robot swarms. Swarm Intell. 2, 97–120 (2008)
Turgut, A.E., Gokce, F., Celikkanat, H., Bayindir, L., Sahin, E.: Kobot: A mobile robot designed specifically for swarm robotics research. Middle East Technical University, Ankara, Turkey, METU-CENG-TR Tech. Rep., vol. 5, no. 2007 (2007)
Amjadi, A., Raoufi, M., Turgut, A.E., Broughton, G., Krajnik, T., Arvin, F.: Cooperative pollution source exploration and cleanup with a bio-inspired swarm robot aggregation. In: International Conference on Collaborative Computing, pp. 469–481 (2020)
Na, S., et al.: Bio-inspired artificial pheromone system for swarm robotics applications. Adapt. Behav. 1059712320918936 (2020)
Arvin, F., Espinosa, J., Bird, B., West, A., Watson, S., Lennox, B.: Mona: An affordable open-source mobile robot for education and research. J. Intell. Robot. Syst. 94(3–4), 761–775 (2019)
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: Towards Autonomous Robotic Systems, pp. 263–274 (2019)
Karimi, A., Nobahari, H., Siarry, P.: Continuous ant colony system and tabu search algorithms hybridized for global minimization of continuous multi-minima functions. Comput. Optimiz. Appl. 45, 639–661 (2010)
Bahaidarah, M., Rekabi-Bana, F., Turgut, A.E., Marjanovic, O., Arvin, F.: Optimization of a self-organized collective motion in a robotic swarm. In: Swarm Intelligence: 13th International Conference, ANTS 2022, pp. 341–349 (2022)
Ban, Z., Hu, J., Lennox, B., Arvin, F.: Self-organised collision-free flocking mechanism in heterogeneous robot swarms. Mob. Netw. Appl. 1–11 (2021)
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)
Fossen, T.I., Fjellstad, O.-E.: Nonlinear modelling of marine vehicles in 6 degrees of freedom. Math. Model. Syst. 1(1), 17–27 (1995)
Groves, K., Dimitrov, M., Peel, H., Marjanovic, O., Lennox, B.: Model identification of a small omnidirectional aquatic surface vehicle: A practical implementation. In: International Conference on Intelligent Robots and Systems (IROS), pp. 1813–1818 (2020)
He, Y., Lennox, B., Arvin, F.: Exploration of underwater storage facilities with swarm of micro-surface robots. In: Towards Autonomous Robotic Systems, pp. 92–104 (2022)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
He, Y., Yao, K., Lennox, B., Arvin, F. (2023). Exploration of Underwater Environments with a Swarm of Heterogeneous Surface Robots. In: Tan, Y., Shi, Y., Luo, W. (eds) Advances in Swarm Intelligence. ICSI 2023. Lecture Notes in Computer Science, vol 13969. Springer, Cham. https://doi.org/10.1007/978-3-031-36625-3_3
Download citation
DOI: https://doi.org/10.1007/978-3-031-36625-3_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-36624-6
Online ISBN: 978-3-031-36625-3
eBook Packages: Computer ScienceComputer Science (R0)