DC Field | Value | Language |
---|---|---|
dc.contributor.author | SeongJoo Han | - |
dc.contributor.author | Oh, SY | - |
dc.date.accessioned | 2016-04-01T01:25:30Z | - |
dc.date.available | 2016-04-01T01:25:30Z | - |
dc.date.created | 2009-08-19 | - |
dc.date.issued | 2008-03 | - |
dc.identifier.issn | 0941-0643 | - |
dc.identifier.other | 2008-OAK-0000007549 | - |
dc.identifier.uri | https://oasis.postech.ac.kr/handle/2014.oak/22899 | - |
dc.description.abstract | A new approach to the design of a neural network (NN) based navigator is proposed in which the mobile robot travels to a pre-defined goal position safely and efficiently without any prior map of the environment. This navigator can be optimized for any user-defined objective function through the use of an evolutionary algorithm. The motivation of this research is to develop an efficient methodology for general goal-directed navigation in generic indoor environments as opposed to learning specialized primitive behaviors in a limited environment. To this end, a modular NN has been employed to achieve the necessary generalization capability across a variety of indoor environments. Herein, each NN module takes charge of navigating in a specialized local environment, which is the result of decomposing the whole path into a sequence of local paths through clustering of all the possible environments. We verify the efficacy of the proposed algorithm over a variety of both simulated and real unstructured indoor environments using our autonomous mobile robot platform. | - |
dc.description.statementofresponsibility | X | - |
dc.language | English | - |
dc.publisher | SPRINGER | - |
dc.relation.isPartOf | NEURAL COMPUTING & APPLICATIONS | - |
dc.subject | reactive navigation | - |
dc.subject | evolutionary robotics | - |
dc.subject | neurocontroller | - |
dc.subject | environment classification | - |
dc.subject | cooperative coordination | - |
dc.subject | TIME OBSTACLE AVOIDANCE | - |
dc.subject | BEHAVIOR | - |
dc.title | An optimized modular neural network controller based on environment classification and selective sensor usage for mobile robot reactive navigation | - |
dc.type | Article | - |
dc.contributor.college | 전자전기공학과 | - |
dc.identifier.doi | 10.1007/S00521-006-0 | - |
dc.author.google | Han, SJ | - |
dc.author.google | Oh, SY | - |
dc.relation.volume | 17 | - |
dc.relation.issue | 2 | - |
dc.relation.startpage | 161 | - |
dc.relation.lastpage | 173 | - |
dc.contributor.id | 10071831 | - |
dc.relation.journal | NEURAL COMPUTING & APPLICATIONS | - |
dc.relation.index | SCI급, SCOPUS 등재논문 | - |
dc.relation.sci | SCIE | - |
dc.collections.name | Journal Papers | - |
dc.type.rims | ART | - |
dc.identifier.bibliographicCitation | NEURAL COMPUTING & APPLICATIONS, v.17, no.2, pp.161 - 173 | - |
dc.identifier.wosid | 000253522700009 | - |
dc.date.tcdate | 2019-01-01 | - |
dc.citation.endPage | 173 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 161 | - |
dc.citation.title | NEURAL COMPUTING & APPLICATIONS | - |
dc.citation.volume | 17 | - |
dc.contributor.affiliatedAuthor | Oh, SY | - |
dc.identifier.scopusid | 2-s2.0-39749126220 | - |
dc.description.journalClass | 1 | - |
dc.description.journalClass | 1 | - |
dc.description.wostc | 6 | - |
dc.type.docType | Article; Proceedings Paper | - |
dc.subject.keywordAuthor | reactive navigation | - |
dc.subject.keywordAuthor | evolutionary robotics | - |
dc.subject.keywordAuthor | neurocontroller | - |
dc.subject.keywordAuthor | environment classification | - |
dc.subject.keywordAuthor | cooperative coordination | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
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