Table of Contents
ISRN Robotics
Volume 2013, Article ID 608164, 10 pages
http://dx.doi.org/10.5402/2013/608164
Review Article

An Introduction to Swarm Robotics

ETSI Industriales, Universidad Politécnica de Madrid, c/José Gutiérrez Abascal, 2, 28006 Madrid, Spain

Received 18 April 2012; Accepted 19 June 2012

Academic Editors: C. A. G. Soerensen and A. Zavala-Rio

Copyright © 2013 Iñaki Navarro and Fernando Matía. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [38 citations]

The following is the list of published articles that have cited the current article.

  • Anna T. Lawniczak, Leslie Ly, Fei Yu, and Shengkun Xie, “Effects of model parameter interactions on Naïve creatures' success of learning to cross a highway,” 2016 IEEE Congress on Evolutionary Computation (CEC), pp. 693–702, . View at Publisher · View at Google Scholar
  • Aaron Roggow, Georges El-Howayek, and Sami Khorbotly, “Autonomous identification of local agents in multi-agent robotic swarms,” 2016 IEEE International Conference on Electro Information Technology (EIT), pp. 0170–0173, . View at Publisher · View at Google Scholar
  • Argel A. Bandala, Ryan Rhay P. Vicerra, and Elmer P. Dadios, “Adaptive aggregation algorithm for target enclosure implemented in quadrotor unmanned aerial vehicle (QUAV) swarm,” 2014 International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM), pp. 1–5, . View at Publisher · View at Google Scholar
  • Lev V. Utkin, Vladimir S. Zaborovsky, Alexey A. Lukashin, Sergey G. Popov, and Anna V. Podolskaja, “A Siamese Autoencoder Preserving Distances for Anomaly Detection in Multi-robot Systems,” 2017 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO), pp. 39–44, . View at Publisher · View at Google Scholar
  • Elmer R. Magsino, Franchesca Agatha V. Beltran, Hazel Anne P. Cruzat, and Gia Nadine M. De Sagun, “Simulation of search-and-rescue and target surrounding algorithm techniques using Kilobots,” 2016 2nd International Conference on Control, Automation and Robotics (ICCAR), pp. 70–74, . View at Publisher · View at Google Scholar
  • Nyayu Latifah Husni, Ade Silvia Handayani, Siti Nurmaini, and Irsyadi Yani, “Cooperative searching strategy for swarm robot,” 2017 International Conference on Electrical Engineering and Computer Science (ICECOS), pp. 92–97, . View at Publisher · View at Google Scholar
  • Stefan Herbrechtsmeier, Timo Korthals, Thomas Schopping, and Ulrich Ruckert, “AMiRo: A modular & customizable open-source mini robot platform,” 2016 20th International Conference on System Theory, Control and Computing (ICSTCC), pp. 687–692, . View at Publisher · View at Google Scholar
  • Midhun Vijay, M. M. Kuber, and K. Sivayazi, “Received signal strength based dispersion of swarm of autonomous ground vehicles,” 2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), pp. 52–57, . View at Publisher · View at Google Scholar
  • L. V. Utkin, Yu. A. Zhuk, and V. S. Zaborovsky, “An anomalous behavior detection of a robot system by using a hierarchical Siamese neural network,” 2017 XX IEEE International Conference on Soft Computing and Measurements (SCM), pp. 630–634, . View at Publisher · View at Google Scholar
  • Matthew Stender, Yanjun Yan, H. Bora Karayaka, Peter Tay, and Robert Adams, “Simulating micro-robots to find a point of interest under noise and with limited communication using Particle Swarm Optimization,” SoutheastCon 2017, pp. 1–8, . View at Publisher · View at Google Scholar
  • Argel A. Bandala, Ryan Rhay P. Vicerra, and Elmer P. Dadios, “Formation stabilization algorithm for swarm tracking in unmanned aerial vehicle (UAV) quadrotors,” TENCON 2014 - 2014 IEEE Region 10 Conference, pp. 1–6, . View at Publisher · View at Google Scholar
  • Gerard Ely Faelden, Jose Martin Maningo, Reiichiro Christian Nakano, Argel Bandala, Ryan Rhay Vicerra, and Elmer Dadios, “Implementation of swarm aggregation in quadrotor swarms using an artificial potential function model,” 2016 IEEE Region 10 Conference (TENCON), pp. 2021–2026, . View at Publisher · View at Google Scholar
  • Jose Martin Z. Maningo, Gerard Ely U. Faelden, Reiichiro Christian S. Nakano, Argel A. Bandala, Ryan Rhay P. Vicerra, and Elmer P. Dadios, “Formation control in quadrotor swarm aggregation using Smoothed Particle Hydrodynamics,” 2016 IEEE Region 10 Conference (TENCON), pp. 2070–2075, . View at Publisher · View at Google Scholar
  • Christian Kyle Y. Fermin, Arthur Lanz L. Imperial, Karlo Felipe D. L. Molato, Jesse Daniel A. Santos, Gerard Ely U. Faelden, Jose Martin Z. Maningo, and Argel A. Bandala, “Development and implementation of swarm sweep cleaning protocol for quadrotor unmanned aerial vehicle (QUAV) swarm,” TENCON 2017 - 2017 IEEE Region 10 Conference, pp. 1988–1991, . View at Publisher · View at Google Scholar
  • M. H. A. Majid, and M. R. Arshad, “Underwater acoustic source localization strategy by a group of autonomous surface vehicles,” 2016 IEEE International Conference on Underwater System Technology: Theory and Applications (USYS), pp. 26–31, . View at Publisher · View at Google Scholar
  • Jean-Guillaume J. Durand, Frederic Burgaud, K. D. Cooksey, and Dimitri N. Mavris, “A Methodology to Evaluate Tradeoffs between Individual Architecture Development and Numerality to Achieve Group Performance in Robotics Swarms,” 17th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, . View at Publisher · View at Google Scholar
  • Jean-Guillaume J. Durand, Frederic Burgaud, Kenneth D. Cooksey, and Dimitri N. Mavris, “A Design Optimization Technique for Multi-Robot Systems,” 55th AIAA Aerospace Sciences Meeting, . View at Publisher · View at Google Scholar
  • Samy M. Amin, Karim Ibrahem, Ahmed Al-Naggar, Ashraf Nabil, Ahmed El-Sadek, Mahmoud Abdel-Galil, and Ashraf H. Badawi, “Parametrized Experience Exchange in Expert - Fellow Swarm Robotic System, Controller Performance Context,” AIAA Information Systems-AIAA Infotech @ Aerospace, . View at Publisher · View at Google Scholar
  • Madhubhashi Senanayake, Ilankaikone Senthooran, Jan Carlo Barca, Hoam Chung, Joarder Kamruzzaman, and Manzur Murshed, “Search and tracking algorithms for swarms of robots: A survey,” Robotics and Autonomous Systems, 2015. View at Publisher · View at Google Scholar
  • Levent Bayındır, “A review of swarm robotics tasks,” Neurocomputing, 2015. View at Publisher · View at Google Scholar
  • Luneque Silva, and Nadia Nedjah, “Wave Algorithm for Recruitment in Swarm Robotics,” Computational Science and Its Applications -- ICCSA 2015, vol. 9156, pp. 3–13, 2015. View at Publisher · View at Google Scholar
  • Eugene Kagan, and Irad Ben-Gal, “Bibliography,” Search and Foraging, pp. 225–236, 2015. View at Publisher · View at Google Scholar
  • Payam Zahadat, Sibylle Hahshold, Ronald Thenius, Karl Crailsheim, and Thomas Schmickl, “From honeybees to robots and back: division of labour based on partitioning social inhibition,” Bioinspiration & Biomimetics, vol. 10, no. 6, pp. 066005, 2015. View at Publisher · View at Google Scholar
  • Luneque Silva Junior, and Nadia Nedjah, “Wave Algorithm Applied to Collective Navigation of Robotic Swarms,” Applied Soft Computing, 2016. View at Publisher · View at Google Scholar
  • Payam Zahadat, and Thomas Schmickl, “Division of labor in a swarm of autonomous underwater robots by improved partitioning social inhibition,” Adaptive Behavior, vol. 24, no. 2, pp. 87–101, 2016. View at Publisher · View at Google Scholar
  • Luneque Silva Junior, and Nadia Nedjah, “Efficient Strategy for Collective Navigation Control in Swarm Robotics,” Procedia Computer Science, vol. 80, pp. 814–823, 2016. View at Publisher · View at Google Scholar
  • Ján Zelenka, Tomáš Kasanický, and Ivana Budinská, “A Self-adapting Method for 3D Environment Exploration Inspired by Swarm Behaviour,” Advances in Service and Industrial Robotics, vol. 49, pp. 493–502, 2017. View at Publisher · View at Google Scholar
  • Jos? Guerrero, ?scar Valero, and Gabriel Oliver, “Toward a Possibilistic Swarm Multi-robot Task Allocation: Theoretical and Experimental Results,” Neural Processing Letters, 2017. View at Publisher · View at Google Scholar
  • Ada-Rhodes Short, Ann D. Lai, and Douglas L. Van Bossuyt, “Conceptual design of sacrificial sub-systems: failure flow decision functions,” Research in Engineering Design, 2017. View at Publisher · View at Google Scholar
  • Andrew Jones, and Jeremy Straub, “Concepts for 3D Printing-Based Self-Replicating Robot Command and Coordination Techniques,” Machines, vol. 5, no. 2, pp. 12, 2017. View at Publisher · View at Google Scholar
  • L. V. Utkin, V. S. Zaborovskii, and S. G. Popov, “Detection of anomalous behavior in a robot system based on deep learning elements,” Automatic Control and Computer Sciences, vol. 50, no. 8, pp. 726–733, 2017. View at Publisher · View at Google Scholar
  • David Dovrat, and Alfred M. Bruckstein, “On Gathering and Control of Unicycle A(ge)nts with Crude Sensing Capabilities,” IEEE Intelligent Systems, vol. 32, no. 6, pp. 40–46, 2017. View at Publisher · View at Google Scholar
  • Aufar Zakiev, Tatyana Tsoy, and Evgeni Magid, “Swarm Robotics: Remarks on Terminology and Classification,” Interactive Collaborative Robotics, vol. 11097, pp. 291–300, 2018. View at Publisher · View at Google Scholar
  • Inmo Jang, Hyo-Sang Shin, Antonios Tsourdos, Junho Jeong, Seungkeun Kim, and Jinyoung Suk, “An integrated decision-making framework of a heterogeneous aerial robotic swarm for cooperative tasks with minimum requirements,” Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, pp. 095441001877262, 2018. View at Publisher · View at Google Scholar
  • Nadia Nedjah, and Luneque Silva Junior, “Review of methodologies and tasks in swarm robotics towards standardization,” Swarm and Evolutionary Computation, pp. 100565, 2019. View at Publisher · View at Google Scholar
  • Constantino G. Ribeiro, Luciano Santos Constantin Raptopoulos, and Max Suell Dutra, “An Autonomous Airship Swarm for Maritime Patrol,” Developments and Advances in Defense and Security, vol. 152, pp. 307–320, 2019. View at Publisher · View at Google Scholar
  • Meetha V. Shenoy, Anupama Karuppiah, and Narayan Manjarekar, “A lightweight ANN based robust localization technique for rapid deployment of autonomous systems,” Journal of Ambient Intelligence and Humanized Computing, 2019. View at Publisher · View at Google Scholar
  • M. Matta, G.C. Cardarilli, L. Di Nunzio, R. Fazzolari, D. Giardino, M. Re, F. Silvestri, and S. Spanò, “Q-RTS: a real-time swarm intelligence based on multi-agent Q-learning,” Electronics Letters, 2019. View at Publisher · View at Google Scholar