{"title":"Generating anticipation in robot motion","authors":"M. Gielniak, A. Thomaz","doi":"10.1109/ROMAN.2011.6005255","DOIUrl":null,"url":null,"abstract":"Robots that display anticipatory motion provide their human partners with greater time to respond in interactive tasks because human partners are aware of robot intent earlier. We create anticipatory motion autonomously from a single motion exemplar by extracting hand and body symbols that communicate motion intent and moving them earlier in the motion. We validate that our algorithm extracts the most salient frame (i.e. the correct symbol) which is the most informative about motion intent to human observers. Furthermore, we show that anticipatory variants allow humans to discern motion intent sooner than motions without anticipation, and that humans are able to reliably predict motion intent prior to the symbol frame when motion is anticipatory. Finally, we quantified the time range for robot motion when humans can perceive intent more accurately and the collaborative social benefits of anticipatory motion are greatest.","PeriodicalId":408015,"journal":{"name":"2011 RO-MAN","volume":"151 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"72","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 RO-MAN","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROMAN.2011.6005255","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 72
Abstract
Robots that display anticipatory motion provide their human partners with greater time to respond in interactive tasks because human partners are aware of robot intent earlier. We create anticipatory motion autonomously from a single motion exemplar by extracting hand and body symbols that communicate motion intent and moving them earlier in the motion. We validate that our algorithm extracts the most salient frame (i.e. the correct symbol) which is the most informative about motion intent to human observers. Furthermore, we show that anticipatory variants allow humans to discern motion intent sooner than motions without anticipation, and that humans are able to reliably predict motion intent prior to the symbol frame when motion is anticipatory. Finally, we quantified the time range for robot motion when humans can perceive intent more accurately and the collaborative social benefits of anticipatory motion are greatest.