A Systematic Review of Swarm Robots
Iroju Olaronke, Ikono Rhoda, Ishaya Gambo, Ojerinde Oluwaseun, Olaleke Janet
Current Journal of Applied Science and Technology · pp. 79–97 · Published 18 Jun 2020
10.9734/cjast/2020/v39i1530719Abstract
Advances in robotics have paved the way for a novel approach of organizing large numbers of robots, otherwise referred to as multi-robots. Multi-robots can either be homogenous or heterogeneous. Nevertheless, a group of autonomous and relatively homogenous robots that interacts with one another as well as with their environment is referred to as swarm robots. Swarm robots are biologically inspired by natural swarms as found in animal societies such as birds and fishes as well as social insects such as honey bees, wasps, termites and ants. Hence, they exhibit certain properties which are similar to those found in these creatures such as aggregation, self-organization, foraging as well as flocking. Swarm robots work together to achieve a desired goal, which is usually too complex for a single robot to accomplish. They are typically characterized by simplicity of individuals, fault tolerance, autonomy, parallelism, high reliability, scalability as well as robustness. They can be used for mining, military, medical and agricultural activities. They can also be used for search and rescue missions, toxic waste cleanup, and for piling sandbags along coastlines in preparation for floods or hurricane. Nevertheless, swarm robots are plagued with the stigma of widespread, interference, uncertainty, safety and lack of reliable communication. Furthermore, studies in swarm robotics are practically limited to virtual reality simulations. Hence, the principles of swarm robotics are rarely applied to real-life problems. It is against this background that this study systematically explores swarm robots. This study reviewed eighty literatures relating to swarm robots. These literatures were obtained from journal articles, technical reports, books, and conference proceedings. The selection of these literatures was based on their relevance to the research problem. This study revealed that the application of swarm robots to real life problems would promote the development of systems that are robust, fault tolerant and scalable.
Cited by 23
Virginia Ruiz Garate, Soheil Gholami, Arash Ajoudani · IEEE Transactions on Robotics · 2021
Anton Klarin, Pi-Shen Seet, Janice Jones · Thinking Swarms · 2025
Yunes Alqudsi, Murat Makaraci · Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science · 2024
Krishna Vamshi Ganduri, Bhargav Prajwal Pathri · Journal of Field Robotics · 2024
Aymeric Hénard, Jérémy Rivière, Etienne Peillard · Adaptive Behavior · 2023
Yehia A. Soliman, Sarah N. Abdulkader, Taha M. Mohamed · PeerJ Computer Science · 2021
Matúš Smolko, Peter Papcun, Ján Vaščák · 2024 IEEE 22nd World Symposium on Applied Machine Intelligence and Informatics (SAMI) · 2024
Paulo Rezeck, Héctor Azpúrua, Maurício F. S. Corrêa · Autonomous Robots · 2023
Shu Leng, Zihan Li, Yifeng Shao · Advanced Robotics Research · 2025
Jo Ann Oravec · Social and Cultural Studies of Robots and AI · 2022
Showing 20 of 23 known citations — external sources report more than can currently be individually listed.
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