A collective intelligence model for swarm robotics applications
Abstract Swarm intelligence models represent a powerful tool to address complex tasks by multi-agent systems, although they are rarely used in practical applications as decentralized cooperation logic. Modern challenges include the improvement of model reliability with small swarm sizes and enhancin...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-61985-7 |
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| _version_ | 1849764031392382976 |
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| author | Alessandro Nitti Marco D. de Tullio Ivan Federico Giuseppe Carbone |
| author_facet | Alessandro Nitti Marco D. de Tullio Ivan Federico Giuseppe Carbone |
| author_sort | Alessandro Nitti |
| collection | DOAJ |
| description | Abstract Swarm intelligence models represent a powerful tool to address complex tasks by multi-agent systems, although they are rarely used in practical applications as decentralized cooperation logic. Modern challenges include the improvement of model reliability with small swarm sizes and enhancing performance with minimal number of free parameters. Available techniques are generally tuned for computational optimization, at the expense of the applicability to real-world scenarios. Merging concepts from meta-heuristic methods and consensus theory we propose a swarm cooperation model which can act both as virtual optimizer and vehicle controller. The model shows a higher or equal success rate with respect to benchmark methods on 22 out of 33 landscapes when dealing with less equal 16 agents and low dimensional problems. Beyond multimodal optimization, a computational proof of concept shows that the method can successfully drive the contaminant localization in a complex marine environment by controlling a group of autonomous underwater vehicles. |
| format | Article |
| id | doaj-art-9f5fdbd8bc4c49df9c7cd4012c27e75d |
| institution | DOAJ |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-9f5fdbd8bc4c49df9c7cd4012c27e75d2025-08-20T03:05:14ZengNature PortfolioNature Communications2041-17232025-07-0116111010.1038/s41467-025-61985-7A collective intelligence model for swarm robotics applicationsAlessandro Nitti0Marco D. de Tullio1Ivan Federico2Giuseppe Carbone3Department of Mechanics Mathematics and Management, Polytechnic University of BariDepartment of Mechanics Mathematics and Management, Polytechnic University of BariCMCC Foundation - Euro-Mediterranean Center on Climate ChangeDepartment of Mechanics Mathematics and Management, Polytechnic University of BariAbstract Swarm intelligence models represent a powerful tool to address complex tasks by multi-agent systems, although they are rarely used in practical applications as decentralized cooperation logic. Modern challenges include the improvement of model reliability with small swarm sizes and enhancing performance with minimal number of free parameters. Available techniques are generally tuned for computational optimization, at the expense of the applicability to real-world scenarios. Merging concepts from meta-heuristic methods and consensus theory we propose a swarm cooperation model which can act both as virtual optimizer and vehicle controller. The model shows a higher or equal success rate with respect to benchmark methods on 22 out of 33 landscapes when dealing with less equal 16 agents and low dimensional problems. Beyond multimodal optimization, a computational proof of concept shows that the method can successfully drive the contaminant localization in a complex marine environment by controlling a group of autonomous underwater vehicles.https://doi.org/10.1038/s41467-025-61985-7 |
| spellingShingle | Alessandro Nitti Marco D. de Tullio Ivan Federico Giuseppe Carbone A collective intelligence model for swarm robotics applications Nature Communications |
| title | A collective intelligence model for swarm robotics applications |
| title_full | A collective intelligence model for swarm robotics applications |
| title_fullStr | A collective intelligence model for swarm robotics applications |
| title_full_unstemmed | A collective intelligence model for swarm robotics applications |
| title_short | A collective intelligence model for swarm robotics applications |
| title_sort | collective intelligence model for swarm robotics applications |
| url | https://doi.org/10.1038/s41467-025-61985-7 |
| work_keys_str_mv | AT alessandronitti acollectiveintelligencemodelforswarmroboticsapplications AT marcoddetullio acollectiveintelligencemodelforswarmroboticsapplications AT ivanfederico acollectiveintelligencemodelforswarmroboticsapplications AT giuseppecarbone acollectiveintelligencemodelforswarmroboticsapplications AT alessandronitti collectiveintelligencemodelforswarmroboticsapplications AT marcoddetullio collectiveintelligencemodelforswarmroboticsapplications AT ivanfederico collectiveintelligencemodelforswarmroboticsapplications AT giuseppecarbone collectiveintelligencemodelforswarmroboticsapplications |