Academic Journal
Trajectory tracking optimization of mobile robot using artificial immune system.
| Τίτλος: | Trajectory tracking optimization of mobile robot using artificial immune system. |
|---|---|
| Συγγραφείς: | Cho, Seongsoo, Shrestha, Bhanu, Jang, Wook, Seo, Changho |
| Πηγή: | Multimedia Tools & Applications; Feb2019, Vol. 78 Issue 3, p3203-3220, 18p |
| Θεματικοί όροι: | Immunocomputers, Mobile robots, Robot motion, Artificial intelligence, Robotics |
| Περίληψη: | In this paper, an optimization method that provides quick response using artificial immune system, is proposed and applied to a mobile robot for trajectory tracking. The study focuses on the immune theory to derive a quick optimization method that puts emphasis on immunity feedback using memory cells by the expansion and suppression of the test group rather than to derive a specific mathematical model of the artificial immune system. Various trajectories were selected in mobile environment to evaluate the performance of the proposed artificial immune system. The global inputs to the mobile robot are reference position and reference velocity, which are time variables. The global output of mobile robot is a current position. The tracking controller makes position error to be converged to zero. In order to reduce position error, compensation velocities on the track of trajectory are necessary. Input variables of fuzzy are position errors in every sampling time. The output values of fuzzy are compensation velocities. Immune algorithm is implemented to adjust the scaling factor of fuzzy automatically. The results of the computer simulation proved the system to be efficient and effective for tracing the trajectory to the final destination by the mobile robot. [ABSTRACT FROM AUTHOR] |
| Copyright of Multimedia Tools & Applications is the property of Springer Nature 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.) | |
| Βάση Δεδομένων: | Complementary Index |
| FullText | Links: – Type: other Text: Availability: 0 CustomLinks: – Url: https://dx.doi.org/doi:10.1007/s11042-018-6413-7 Name: EDS - Springer Nature Journals (s7799221) Category: fullText Text: View record at Springer |
|---|---|
| Header | DbId: edb DbLabel: Complementary Index An: 134585430 RelevancyScore: 874 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 873.721008300781 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Trajectory tracking optimization of mobile robot using artificial immune system. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Cho%2C+Seongsoo%22">Cho, Seongsoo</searchLink><br /><searchLink fieldCode="AR" term="%22Shrestha%2C+Bhanu%22">Shrestha, Bhanu</searchLink><br /><searchLink fieldCode="AR" term="%22Jang%2C+Wook%22">Jang, Wook</searchLink><br /><searchLink fieldCode="AR" term="%22Seo%2C+Changho%22">Seo, Changho</searchLink> – Name: TitleSource Label: Source Group: Src Data: Multimedia Tools & Applications; Feb2019, Vol. 78 Issue 3, p3203-3220, 18p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Immunocomputers%22">Immunocomputers</searchLink><br /><searchLink fieldCode="DE" term="%22Mobile+robots%22">Mobile robots</searchLink><br /><searchLink fieldCode="DE" term="%22Robot+motion%22">Robot motion</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Robotics%22">Robotics</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In this paper, an optimization method that provides quick response using artificial immune system, is proposed and applied to a mobile robot for trajectory tracking. The study focuses on the immune theory to derive a quick optimization method that puts emphasis on immunity feedback using memory cells by the expansion and suppression of the test group rather than to derive a specific mathematical model of the artificial immune system. Various trajectories were selected in mobile environment to evaluate the performance of the proposed artificial immune system. The global inputs to the mobile robot are reference position and reference velocity, which are time variables. The global output of mobile robot is a current position. The tracking controller makes position error to be converged to zero. In order to reduce position error, compensation velocities on the track of trajectory are necessary. Input variables of fuzzy are position errors in every sampling time. The output values of fuzzy are compensation velocities. Immune algorithm is implemented to adjust the scaling factor of fuzzy automatically. The results of the computer simulation proved the system to be efficient and effective for tracing the trajectory to the final destination by the mobile robot. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Multimedia Tools & Applications is the property of Springer Nature 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.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edb&AN=134585430 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11042-018-6413-7 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 18 StartPage: 3203 Subjects: – SubjectFull: Immunocomputers Type: general – SubjectFull: Mobile robots Type: general – SubjectFull: Robot motion Type: general – SubjectFull: Artificial intelligence Type: general – SubjectFull: Robotics Type: general Titles: – TitleFull: Trajectory tracking optimization of mobile robot using artificial immune system. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Cho, Seongsoo – PersonEntity: Name: NameFull: Shrestha, Bhanu – PersonEntity: Name: NameFull: Jang, Wook – PersonEntity: Name: NameFull: Seo, Changho IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Feb2019 Type: published Y: 2019 Identifiers: – Type: issn-print Value: 13807501 Numbering: – Type: volume Value: 78 – Type: issue Value: 3 Titles: – TitleFull: Multimedia Tools & Applications Type: main |
| ResultId | 1 |