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dc.contributor.authorDahl, TS
dc.contributor.authorPierris, G
dc.date.accessioned2017-01-17T22:06:47Z
dc.date.available2017-01-17T22:06:47Z
dc.date.issued2017-01-17
dc.identifier.issn2379-8920
dc.identifier.issn2379-8939
dc.identifier.urihttp://hdl.handle.net/10026.1/8257
dc.description.abstract

Hierarchical representations and modeling of sensorimotor observations is a fundamental approach for the development of scalable robot control strategies. Previously, we introduced the novel Hierarchical Self-Organizing Map-based Encoding algorithm (HSOME) that is based on a computational model of infant cognition. Each layer is a temporally augmented SOM and every node updates a decaying activation value. The bottom level encodes sensori-motor instances while their temporal associations are hierarchically built on the layers above. In the past, HSOME has shown to support hierarchical encoding of sequential sensor-actuator observations both in abstract domains and real humanoid robots. Two novel features are presented here starting with the novel skill acquisition in the complex domain of learning a double tap tactile gesture between two humanoid robots. During reproduction, the robot can either perform a double tap or prioritize to receive a higher reward by performing a single tap instead. Secondly, HSOME has been extended to recall past observations and reproduce rhythmic patterns in the absence of input relevant to the joints by priming initially the reproduction of specific skills with an input. We also demonstrate in simulation how a complex behavior emerges from the automatic reuse of distinct oscillatory swimming demonstrations of a robotic salamander.

dc.format.extent30-43
dc.language.isoen
dc.publisherIEEE
dc.subjectArtificial neural networks
dc.subjectrobot programming by demonstration (PbD)
dc.subjectself-organizing maps (SOMs)
dc.subjecttactile gestures.
dc.titleLearning Robot Control using a Hierarchical SOM-based Encoding
dc.typejournal-article
dc.typeArticle
plymouth.issue1
plymouth.volume9
plymouth.publisher-urlhttp://dx.doi.org/10.1109/tcds.2017.2657744
plymouth.publication-statusPublished
plymouth.journalIEEE Transactions on Cognitive and Developmental Systems
dc.identifier.doi10.1109/tcds.2017.2657744
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering
plymouth.organisational-group/Plymouth/Research Groups
plymouth.organisational-group/Plymouth/Research Groups/Institute of Health and Community
plymouth.organisational-group/Plymouth/Users by role
dcterms.dateAccepted2016-12-10
dc.identifier.eissn2379-8939
dc.rights.embargoperiodNot known
rioxxterms.versionofrecord10.1109/tcds.2017.2657744
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2017-01-17
rioxxterms.typeJournal Article/Review


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