Optimizing soft robot design and tracking with and without evolutionary computation: an intensive survey

dc.authorscopusid54891556200
dc.authorscopusid59345513700
dc.authorscopusid59345694600
dc.authorscopusid57205209268
dc.authorscopusid55807561700
dc.authorwosidBaran, Eray/ABY-5828-2022
dc.contributor.authorStroppa, Fabıo
dc.contributor.authorSaraç Stroppa, Mine
dc.contributor.authorBatiya, Jana
dc.contributor.authorBaran, Eray
dc.contributor.authorSarac, Mine
dc.date.accessioned2024-10-15T19:40:34Z
dc.date.available2024-10-15T19:40:34Z
dc.date.issued2024
dc.departmentKadir Has Universityen_US
dc.department-temp[Stroppa, Fabio; Batiya, Jana; Sarac, Mine] Kadir Has Univ, Istanbul, Turkiye; [Majeed, Fatimah Jabbar; Baran, Eray] Istanbul Bilgi Univ, Istanbul, Turkiyeen_US
dc.description.abstractSoft robotic devices are designed for applications such as exploration, manipulation, search and rescue, medical surgery, rehabilitation, and assistance. Due to their complex kinematics, various and often hard-to-define degrees of freedom, and nonlinear properties of their material, designing and operating these devices can be quite challenging. Using tools such as optimization methods can improve the efficiency of these devices and help roboticists manufacture the robots they need. In this work, we present an extensive and systematic literature search on the optimization methods used for the mechanical design of soft robots, particularly focusing on literature exploiting evolutionary computation (EC). We completed the search in the IEEE, ACM, Springer, SAGE, Elsevier, MDPI, Scholar, and Scopus databases between 2009 and 2024 using the keywords "soft robot," "design," and "optimization." We categorized our findings in terms of the type of soft robot (i.e., bio-inspired, cable-driven, continuum, fluid-driven, gripper, manipulator, modular), its application (exploration, manipulation, surgery), the optimization metrics (topology, force, locomotion, kinematics, sensors, and energy), and the optimization method (categorized as EC or non-EC methods). After providing a road map of our findings in the state of the art, we offer our observations concerning the implementation of the optimization methods and their advantages. We then conclude our paper with suggestions for future research.en_US
dc.description.sponsorshipTUBIdot;TAK within the scope of the 2232-B International Fellowship for Early Stage Researchers Program [121C145]en_US
dc.description.sponsorshipThis work is funded by TUB & Idot;TAK within the scope of the 2232-B International Fellowship for Early Stage Researchers Program number 121C145.en_US
dc.description.woscitationindexScience Citation Index Expanded
dc.identifier.citation0
dc.identifier.doi10.1017/S0263574724001152
dc.identifier.issn0263-5747
dc.identifier.issn1469-8668
dc.identifier.scopus2-s2.0-85205089279
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.1017/S0263574724001152
dc.identifier.urihttps://hdl.handle.net/20.500.12469/6371
dc.identifier.wosWOS:001316233200001
dc.identifier.wosqualityQ3
dc.language.isoenen_US
dc.publisherCambridge Univ Pressen_US
dc.relation.publicationcategoryDiğeren_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectdesignen_US
dc.subjectmodular robotsen_US
dc.subjectbiomimetic robotsen_US
dc.subjectgraspingen_US
dc.subjectnavigationen_US
dc.subjectnovel applications of roboticsen_US
dc.subjectredundant manipulatorsen_US
dc.subjectserial manipulator design and kinematicsen_US
dc.subjecttopological modeling of robotsen_US
dc.titleOptimizing soft robot design and tracking with and without evolutionary computation: an intensive surveyen_US
dc.typeReviewen_US
dspace.entity.typePublication
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relation.isAuthorOfPublication6f4bfc6a-f6a1-4ef6-83b0-cd0753a2609b
relation.isAuthorOfPublication.latestForDiscoveryf8babe23-f015-4905-a50a-4e9567f9ee8d

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