Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-16587-0_62
DC FieldValue
dc.titleAdaptive compliance control for collision-tolerant robot arm with viscoelastic trunk
dc.contributor.authorChin, C.
dc.contributor.authorLi, Y.
dc.contributor.authorGe, S.S.
dc.contributor.authorCabibihan, J.-J.
dc.date.accessioned2014-06-19T02:57:32Z
dc.date.available2014-06-19T02:57:32Z
dc.date.issued2010
dc.identifier.citationChin, C.,Li, Y.,Ge, S.S.,Cabibihan, J.-J. (2010). Adaptive compliance control for collision-tolerant robot arm with viscoelastic trunk. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6425 LNAI (PART 2) : 683-694. ScholarBank@NUS Repository. <a href="https://doi.org/10.1007/978-3-642-16587-0_62" target="_blank">https://doi.org/10.1007/978-3-642-16587-0_62</a>
dc.identifier.isbn3642165869
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/69161
dc.description.abstractIn the present work, a collision-tolerant control method was proposed to achieve a stable task performance of the robot arm in an acceptable collision-safe margin. A robot arm covered with the soft capacitive sensing skin mounted on a passive mechanical viscoelastic trunk has been proposed to suppress the unexpected collisions which may happen from anywhere in the social context. The viscoelastic trunk contributed to the passive deformation in response to the collision forces and the joint configurations of the robot arm were directly calculated in accordance to the trunk deformation. An adaptive control scheme has been introduced to achieve a good end-effector trajectory performance upon collisions. Simulation results and actual assessment on a prototype model confirmed the effectiveness of proposed methods. © 2010 Springer-Verlag.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/978-3-642-16587-0_62
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1007/978-3-642-16587-0_62
dc.description.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.description.volume6425 LNAI
dc.description.issuePART 2
dc.description.page683-694
dc.identifier.isiutNOT_IN_WOS
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