Adaptivity: a path towards general swarm intelligence?
The field of multi-robot systems (MRS) has recently been gaining increasing popularity among various research groups, practitioners, and a wide range of industries. Compared to single-robot systems, multi-robot systems are able to perform tasks more efficiently or accomplish objectives that are simp...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-05-01
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| Series: | Frontiers in Robotics and AI |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/frobt.2023.1163185/full |
| _version_ | 1797830998629548032 |
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| author | Hian Lee Kwa Jabez Leong Kit Nikolaj Horsevad Julien Philippot Mohammad Savari Roland Bouffanais |
| author_facet | Hian Lee Kwa Jabez Leong Kit Nikolaj Horsevad Julien Philippot Mohammad Savari Roland Bouffanais |
| author_sort | Hian Lee Kwa |
| collection | DOAJ |
| description | The field of multi-robot systems (MRS) has recently been gaining increasing popularity among various research groups, practitioners, and a wide range of industries. Compared to single-robot systems, multi-robot systems are able to perform tasks more efficiently or accomplish objectives that are simply not feasible with a single unit. This makes such multi-robot systems ideal candidates for carrying out distributed tasks in large environments—e.g., performing object retrieval, mapping, or surveillance. However, the traditional approach to multi-robot systems using global planning and centralized operation is, in general, ill-suited for fulfilling tasks in unstructured and dynamic environments. Swarming multi-robot systems have been proposed to deal with such steep challenges, primarily owing to its adaptivity. These qualities are expressed by the system’s ability to learn or change its behavior in response to new and/or evolving operating conditions. Given its importance, in this perspective, we focus on the critical importance of adaptivity for effective multi-robot system swarming and use it as the basis for defining, and potentially quantifying, swarm intelligence. In addition, we highlight the importance of establishing a suite of benchmark tests to measure a swarm’s level of adaptivity. We believe that a focus on achieving increased levels of swarm intelligence through the focus on adaptivity will further be able to elevate the field of swarm robotics. |
| first_indexed | 2024-04-09T13:45:26Z |
| format | Article |
| id | doaj.art-eb5d7afeba4a44208782c54a43eb79ac |
| institution | Directory Open Access Journal |
| issn | 2296-9144 |
| language | English |
| last_indexed | 2024-04-09T13:45:26Z |
| publishDate | 2023-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Robotics and AI |
| spelling | doaj.art-eb5d7afeba4a44208782c54a43eb79ac2023-05-09T04:58:01ZengFrontiers Media S.A.Frontiers in Robotics and AI2296-91442023-05-011010.3389/frobt.2023.11631851163185Adaptivity: a path towards general swarm intelligence?Hian Lee Kwa0Jabez Leong Kit1Nikolaj Horsevad2Julien Philippot3Mohammad Savari4Roland Bouffanais5Thales Research and Technology, Singapore, SingaporeEngineering Product Design, Singapore University of Technology and Design, Singapore, SingaporeMechanical Engineering, University of Ottawa, Ottawa, ON, CanadaMechanical Engineering, University of Ottawa, Ottawa, ON, CanadaMechanical Engineering, University of Ottawa, Ottawa, ON, CanadaMechanical Engineering, University of Ottawa, Ottawa, ON, CanadaThe field of multi-robot systems (MRS) has recently been gaining increasing popularity among various research groups, practitioners, and a wide range of industries. Compared to single-robot systems, multi-robot systems are able to perform tasks more efficiently or accomplish objectives that are simply not feasible with a single unit. This makes such multi-robot systems ideal candidates for carrying out distributed tasks in large environments—e.g., performing object retrieval, mapping, or surveillance. However, the traditional approach to multi-robot systems using global planning and centralized operation is, in general, ill-suited for fulfilling tasks in unstructured and dynamic environments. Swarming multi-robot systems have been proposed to deal with such steep challenges, primarily owing to its adaptivity. These qualities are expressed by the system’s ability to learn or change its behavior in response to new and/or evolving operating conditions. Given its importance, in this perspective, we focus on the critical importance of adaptivity for effective multi-robot system swarming and use it as the basis for defining, and potentially quantifying, swarm intelligence. In addition, we highlight the importance of establishing a suite of benchmark tests to measure a swarm’s level of adaptivity. We believe that a focus on achieving increased levels of swarm intelligence through the focus on adaptivity will further be able to elevate the field of swarm robotics.https://www.frontiersin.org/articles/10.3389/frobt.2023.1163185/fulladaptivitycollective roboticsmulti-agent systemsmulti-robot systemsswarm roboticsswarm intelligence |
| spellingShingle | Hian Lee Kwa Jabez Leong Kit Nikolaj Horsevad Julien Philippot Mohammad Savari Roland Bouffanais Adaptivity: a path towards general swarm intelligence? Frontiers in Robotics and AI adaptivity collective robotics multi-agent systems multi-robot systems swarm robotics swarm intelligence |
| title | Adaptivity: a path towards general swarm intelligence? |
| title_full | Adaptivity: a path towards general swarm intelligence? |
| title_fullStr | Adaptivity: a path towards general swarm intelligence? |
| title_full_unstemmed | Adaptivity: a path towards general swarm intelligence? |
| title_short | Adaptivity: a path towards general swarm intelligence? |
| title_sort | adaptivity a path towards general swarm intelligence |
| topic | adaptivity collective robotics multi-agent systems multi-robot systems swarm robotics swarm intelligence |
| url | https://www.frontiersin.org/articles/10.3389/frobt.2023.1163185/full |
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