Academic Journal
CSO: A Novel Crow Swarm Optimization Algorithm for Collaborative Path Planning with Collision Avoidance.
| Τίτλος: | CSO: A Novel Crow Swarm Optimization Algorithm for Collaborative Path Planning with Collision Avoidance. |
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| Συγγραφείς: | Laassami, Ferial1 (AUTHOR) ferial.laassami@univ-khenchela.dz, Ledmi, Abdeldjalil1 (AUTHOR), Souidi, Mohammed El Habib1 (AUTHOR) |
| Πηγή: | Journal of Intelligent & Fuzzy Systems. Aug2026, Vol. 50 Issue 8, p2471-2496. 26p. |
| Θεματικοί όροι: | *Accident prevention, Multiagent systems, Robotic path planning, Metaheuristic algorithms, Particle swarm optimization |
| Περίληψη: | For autonomous systems operating in complex environments, it is a critical challenge to develop effective MAS path planning control mechanism that enables agents to collaborate and avoid collisions with each other. In response to this crucial need, this paper introduces a novel hybrid algorithm for MAS path planning called Crow Swarm Optimization (CSO). This solution leverages the strengths of two distinct metaheuristic approaches, the Crow Search algorithm (CSA) and the Particle Swarm Optimization (PSO). Although CSA is effective during search space exploration, it has slower convergence and weaknesses in finding global optima due to random location updates. To enhance the local search capability of the CSA, this research leverages the strength of PSO in exploitation. To accomplish this, the primary objective of this paper is to leverage the functionally segregated mechanism to overcome the inherent weaknesses of single-approach algorithms, thereby achieving optimal MAS path planning. Beyond path optimization, the presented work addresses collision prevention employing a velocity adjustment technique. This approach minimizes the agent's velocity to prevent collisions with other agents. To validate the findings, the study conducted a comparative analysis against various versions of both CSA and PSO. The results clearly demonstrate the efficacy of the proposed approach in solving the path-planning problem with collision avoidance. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Intelligent & Fuzzy Systems is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
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| Items | – Name: Title Label: Title Group: Ti Data: CSO: A Novel Crow Swarm Optimization Algorithm for Collaborative Path Planning with Collision Avoidance. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Laassami%2C+Ferial%22">Laassami, Ferial</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> ferial.laassami@univ-khenchela.dz</i><br /><searchLink fieldCode="AR" term="%22Ledmi%2C+Abdeldjalil%22">Ledmi, Abdeldjalil</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Souidi%2C+Mohammed+El+Habib%22">Souidi, Mohammed El Habib</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Intelligent+%26+Fuzzy+Systems%22">Journal of Intelligent & Fuzzy Systems</searchLink>. Aug2026, Vol. 50 Issue 8, p2471-2496. 26p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Accident+prevention%22">Accident prevention</searchLink><br /><searchLink fieldCode="DE" term="%22Multiagent+systems%22">Multiagent systems</searchLink><br /><searchLink fieldCode="DE" term="%22Robotic+path+planning%22">Robotic path planning</searchLink><br /><searchLink fieldCode="DE" term="%22Metaheuristic+algorithms%22">Metaheuristic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Particle+swarm+optimization%22">Particle swarm optimization</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: For autonomous systems operating in complex environments, it is a critical challenge to develop effective MAS path planning control mechanism that enables agents to collaborate and avoid collisions with each other. In response to this crucial need, this paper introduces a novel hybrid algorithm for MAS path planning called Crow Swarm Optimization (CSO). This solution leverages the strengths of two distinct metaheuristic approaches, the Crow Search algorithm (CSA) and the Particle Swarm Optimization (PSO). Although CSA is effective during search space exploration, it has slower convergence and weaknesses in finding global optima due to random location updates. To enhance the local search capability of the CSA, this research leverages the strength of PSO in exploitation. To accomplish this, the primary objective of this paper is to leverage the functionally segregated mechanism to overcome the inherent weaknesses of single-approach algorithms, thereby achieving optimal MAS path planning. Beyond path optimization, the presented work addresses collision prevention employing a velocity adjustment technique. This approach minimizes the agent's velocity to prevent collisions with other agents. To validate the findings, the study conducted a comparative analysis against various versions of both CSA and PSO. The results clearly demonstrate the efficacy of the proposed approach in solving the path-planning problem with collision avoidance. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Intelligent & Fuzzy Systems is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1177/18758967261422625 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 26 StartPage: 2471 Subjects: – SubjectFull: Accident prevention Type: general – SubjectFull: Multiagent systems Type: general – SubjectFull: Robotic path planning Type: general – SubjectFull: Metaheuristic algorithms Type: general – SubjectFull: Particle swarm optimization Type: general Titles: – TitleFull: CSO: A Novel Crow Swarm Optimization Algorithm for Collaborative Path Planning with Collision Avoidance. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Laassami, Ferial – PersonEntity: Name: NameFull: Ledmi, Abdeldjalil – PersonEntity: Name: NameFull: Souidi, Mohammed El Habib IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 08 Text: Aug2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 10641246 Numbering: – Type: volume Value: 50 – Type: issue Value: 8 Titles: – TitleFull: Journal of Intelligent & Fuzzy Systems Type: main |
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