{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T06:44:23Z","timestamp":1777617863970,"version":"3.51.4"},"reference-count":53,"publisher":"Cambridge University Press (CUP)","issue":"5","license":[{"start":{"date-parts":[[2014,8,19]],"date-time":"2014-08-19T00:00:00Z","timestamp":1408406400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotica"],"published-print":{"date-parts":[[2015,6]]},"abstract":"<jats:title>SUMMARY<\/jats:title><jats:p>Parental scaffolding is an important mechanism that speeds up infant sensorimotor development. Infants pay stronger attention to the features of the objects highlighted by parents, and their manipulation skills develop earlier than they would in isolation due to caregivers' support. Parents are known to make modifications in infant-directed actions, which are often called \u201cmotionese\u201d<jats:sup>7<\/jats:sup>. The features that might be associated with motionese are amplification, repetition and simplification in caregivers' movements, which are often accompanied by increased social signalling. In this paper, we extend our previously developed affordances learning framework to enable our hand-arm robot equipped with a range camera to benefit from parental scaffolding and motionese. We first present our results on how parental scaffolding can be used to guide the robot learning and to modify its crude action execution to speed up the learning of complex skills. For this purpose, an interactive human caregiver-infant scenario was realized with our robotic setup. This setup allowed the caregiver's modification of the ongoing reach and grasp movement of the robot via physical interaction. This enabled the caregiver to make the robot grasp the target object, which in turn could be used by the robot to learn the grasping skill. In addition to this, we also show how parental scaffolding can be used in speeding up imitation learning. We present the details of our work that takes the robot beyond simple goal-level imitation, making it a better imitator with the help of motionese.<\/jats:p>","DOI":"10.1017\/s0263574714002148","type":"journal-article","created":{"date-parts":[[2014,8,19]],"date-time":"2014-08-19T14:04:05Z","timestamp":1408457045000},"page":"1163-1180","source":"Crossref","is-referenced-by-count":19,"title":["Parental scaffolding as a bootstrapping mechanism for learning grasp affordances and imitation skills"],"prefix":"10.1017","volume":"33","author":[{"given":"Emre","family":"Ugur","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yukie","family":"Nagai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hande","family":"Celikkanat","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erhan","family":"Oztop","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"56","published-online":{"date-parts":[[2014,8,19]]},"reference":[{"key":"S0263574714002148_ref52","doi-asserted-by":"publisher","DOI":"10.1111\/j.1469-7610.1976.tb00381.x"},{"key":"S0263574714002148_ref53","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2006.02.029"},{"key":"S0263574714002148_ref50","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2008.07.057"},{"key":"S0263574714002148_ref51","doi-asserted-by":"publisher","DOI":"10.1126\/science.7839147"},{"key":"S0263574714002148_ref48","unstructured":"E. Ugur , E. Sahin and E. Oztop , \u201cAffordance Learning from Range Data for Multi-Step Planning,\u201d Proceedings of the 9th International Conference on Epigenetic Robotics (2009) pp. 177\u2013184."},{"key":"S0263574714002148_ref46","doi-asserted-by":"crossref","unstructured":"E. Ugur , H. Celikkanat , Y. Nagai and E. Oztop , \u201cLearning to Grasp with Parental Scaffolding,\u201d Proceedings of the IEEE International Conference on Humanoid Robotics (2011a) pp. 480\u2013486.","DOI":"10.1109\/Humanoids.2011.6100890"},{"key":"S0263574714002148_ref35","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-8624.2011.01610.x"},{"key":"S0263574714002148_ref34","doi-asserted-by":"crossref","unstructured":"P. Pastor , L. Righetti , M. Kalakrishnan and S. Schaal , \u201cOnline Movement Adaptation Based on Previous Sensor Experiences,\u201d Proceedings of the 2011 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE (2011) pp. 365\u2013371.","DOI":"10.1109\/IROS.2011.6095059"},{"key":"S0263574714002148_ref27","doi-asserted-by":"crossref","first-page":"2580","DOI":"10.1152\/jn.2000.83.5.2580","article-title":"Selectivity for the shape, size, and orientation of objects for grasping in neurons of monkey parietal are AIP","volume":"83","author":"Murata","year":"2000","journal-title":"J. Neuropyhsiology"},{"key":"S0263574714002148_ref30","unstructured":"Y. Nagai and K. J. Rohlfing , \u201cCan Motionese Tell Infants and Robots: What to Imitate?,\u201d Proceedings of the 4th International Symposium on Imitation in Animals and Artifacts, AISB (2007) pp. 299\u2013306."},{"key":"S0263574714002148_ref14","doi-asserted-by":"publisher","DOI":"10.1016\/S0163-6383(85)80005-9"},{"key":"S0263574714002148_ref6","doi-asserted-by":"publisher","DOI":"10.1080\/019697201300001849"},{"key":"S0263574714002148_ref40","doi-asserted-by":"publisher","DOI":"10.1177\/0278364907087172"},{"key":"S0263574714002148_ref49","unstructured":"E. Ugur , E. Sahin and E. Oztop , \u201cSelf-discovery of Motor Primitives and Learning Grasp Affordances,\u201d IEEE\/RSJ International Conference on Intelligent Robots and Systems (2012) pp. 3260\u20133267."},{"key":"S0263574714002148_ref39","doi-asserted-by":"crossref","unstructured":"J. Saunders , C. L. Nehaniv and K. Dautenhahn , \u201cTeaching Robots by Moulding Behavior and Scaffolding the Environment,\u201d Proceedings of the ACM SIGCHI\/SIGART Conference on Human-robot Interaction (2006) pp. 118\u2013125.","DOI":"10.1145\/1121241.1121263"},{"key":"S0263574714002148_ref20","doi-asserted-by":"publisher","DOI":"10.1007\/s10514-013-9366-8"},{"key":"S0263574714002148_ref47","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2011.04.005"},{"key":"S0263574714002148_ref38","doi-asserted-by":"publisher","DOI":"10.5772\/5703"},{"key":"S0263574714002148_ref36","unstructured":"J. Peters , S. Vijayakumar and S. Schaal , \u201cReinforcement Learning for Humanoid Robotics,\u201d Proceedings of the Third IEEE-RAS International Conference on Humanoid Robots (2003) pp. 1\u201320."},{"key":"S0263574714002148_ref11","doi-asserted-by":"publisher","DOI":"10.1177\/1059712307084689"},{"key":"S0263574714002148_ref3","doi-asserted-by":"publisher","DOI":"10.1002\/dev.20280"},{"key":"S0263574714002148_ref42","doi-asserted-by":"publisher","DOI":"10.1007\/4-431-31381-8_23"},{"key":"S0263574714002148_ref16","doi-asserted-by":"publisher","DOI":"10.1007\/s10514-009-9118-y"},{"key":"S0263574714002148_ref8","unstructured":"C. Breazeal , Learning by Scaffolding PhD Thesis, Elec. Eng. Comp. Sci. (MIT, Cambridge, MA, 1999)."},{"key":"S0263574714002148_ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2004.03.003"},{"key":"S0263574714002148_ref5","doi-asserted-by":"crossref","unstructured":"A. Bicchi and V. Kumar , \u201cRobotic Grasping and Contact: A Review,\u201d Proceedings of the IEEE International Conference on Robotics and Automation (2000) pp. 348\u2013353.","DOI":"10.1109\/ROBOT.2000.844081"},{"key":"S0263574714002148_ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2010.2065430"},{"key":"S0263574714002148_ref41","doi-asserted-by":"publisher","DOI":"10.1016\/S1364-6613(99)01327-3"},{"key":"S0263574714002148_ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.infbeh.2009.07.003"},{"key":"S0263574714002148_ref2","doi-asserted-by":"publisher","DOI":"10.1177\/1059712311411112"},{"key":"S0263574714002148_ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.conb.2007.03.004"},{"key":"S0263574714002148_ref17","doi-asserted-by":"publisher","DOI":"10.1038\/415755a"},{"key":"S0263574714002148_ref31","doi-asserted-by":"crossref","unstructured":"Y. Nagai and K. J. Rohlfing , \u201cParental Action Modification Highlighting the Goal versus the Means,\u201d Proceedings of the IEEE 7th International Conference on Development and Learning (2008).","DOI":"10.1109\/DEVLRN.2008.4640796"},{"key":"S0263574714002148_ref37","doi-asserted-by":"publisher","DOI":"10.1163\/156855306778522532"},{"key":"S0263574714002148_ref15","doi-asserted-by":"publisher","DOI":"10.1075\/is.12.1.06fis"},{"key":"S0263574714002148_ref1","doi-asserted-by":"crossref","unstructured":"B. D. Argall , E. L. Sauser and A. G. Billard , \u201cTactile Guidance for Policy Refinement and Reuse,\u201d Proceedings of the 9th IEEE International Conference on Development and Learning (2010) pp. 7\u201312.","DOI":"10.1109\/DEVLRN.2010.5578872"},{"key":"S0263574714002148_ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCB.2006.886952"},{"key":"S0263574714002148_ref4","unstructured":"L. E. Berk and A. Winsler , \u201cScaffolding Children's Learning: Vygotsky and Early Childhood Education,\u201d National Assoc. for Education (1995)."},{"key":"S0263574714002148_ref7","doi-asserted-by":"publisher","DOI":"10.1111\/1467-7687.00211"},{"key":"S0263574714002148_ref10","doi-asserted-by":"publisher","DOI":"10.1111\/1467-8624.00481"},{"key":"S0263574714002148_ref21","doi-asserted-by":"publisher","DOI":"10.2307\/1130128"},{"key":"S0263574714002148_ref25","doi-asserted-by":"publisher","DOI":"10.1016\/0163-6383(92)80013-K"},{"key":"S0263574714002148_ref24","doi-asserted-by":"publisher","DOI":"10.1007\/BF02481317"},{"key":"S0263574714002148_ref29","unstructured":"Y. Nagai , A. Nakatani and M. Asada , \u201cHow a RobotS Attention Shapes the Way People Teach,\u201d Proceedings of the 10th International Conference on Epigenetic Robotics (2010), pp. 81\u201388."},{"key":"S0263574714002148_ref33","first-page":"11","article-title":"Like me? Measures of correspondence and imitation","volume":"32","author":"Nehaniv","year":"2011","journal-title":"Cybern. Syst."},{"key":"S0263574714002148_ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TAMD.2013.2269905"},{"key":"S0263574714002148_ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-05181-4_19"},{"key":"S0263574714002148_ref19","volume-title":"Computer and Robot Vision, Volume I","author":"Haralick","year":"1992"},{"key":"S0263574714002148_ref18","doi-asserted-by":"publisher","DOI":"10.1002\/icd.446"},{"key":"S0263574714002148_ref44","doi-asserted-by":"publisher","DOI":"10.1016\/B978-012273965-1\/50016-9"},{"key":"S0263574714002148_ref13","first-page":"1","article-title":"Learning grasp affordance densities","volume":"2","author":"Detry","year":"2011","journal-title":"Paladyn"},{"key":"S0263574714002148_ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2011.09.002"},{"key":"S0263574714002148_ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TAMD.2009.2021090"}],"container-title":["Robotica"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S0263574714002148","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,4,21]],"date-time":"2019-04-21T00:04:25Z","timestamp":1555805065000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S0263574714002148\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,8,19]]},"references-count":53,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2015,6]]}},"alternative-id":["S0263574714002148"],"URL":"https:\/\/doi.org\/10.1017\/s0263574714002148","relation":{},"ISSN":["0263-5747","1469-8668"],"issn-type":[{"value":"0263-5747","type":"print"},{"value":"1469-8668","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,8,19]]}}}