J. E. Domínguez-Vidal, Nicolás Rodríguez, A. Sanfeliu
{"title":"Perception-Intention-Action Cycle as a Human Acceptable Way for Improving Human-Robot Collaborative Tasks","authors":"J. E. Domínguez-Vidal, Nicolás Rodríguez, A. Sanfeliu","doi":"10.1145/3568294.3580149","DOIUrl":null,"url":null,"abstract":"In Human-Robot Collaboration (HRC) tasks, the classical Perception-Action cycle can not fully explain the collaborative behaviour of the human-robot pair until it is extended to Perception-Intention-Action (PIA) cycle, giving to the human's intention a key role at the same level of the robot's perception and not as a subblock of this. Although part of the human's intention can be perceived or inferred by the other agent, this is prone to misunderstandings so the true intention has to be explicitly informed in some cases to fulfill the task. Here, we explore both types of intention and we combine them with the robot's perception through the concept of Situation Awareness (SA). We validate the PIA cycle and its acceptance by the user with a preliminary experiment in an object transportation task showing that its usage can increase trust in the robot.","PeriodicalId":36515,"journal":{"name":"ACM Transactions on Human-Robot Interaction","volume":"8 1","pages":""},"PeriodicalIF":4.2000,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Human-Robot Interaction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3568294.3580149","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ROBOTICS","Score":null,"Total":0}
引用次数: 0
Abstract
In Human-Robot Collaboration (HRC) tasks, the classical Perception-Action cycle can not fully explain the collaborative behaviour of the human-robot pair until it is extended to Perception-Intention-Action (PIA) cycle, giving to the human's intention a key role at the same level of the robot's perception and not as a subblock of this. Although part of the human's intention can be perceived or inferred by the other agent, this is prone to misunderstandings so the true intention has to be explicitly informed in some cases to fulfill the task. Here, we explore both types of intention and we combine them with the robot's perception through the concept of Situation Awareness (SA). We validate the PIA cycle and its acceptance by the user with a preliminary experiment in an object transportation task showing that its usage can increase trust in the robot.
期刊介绍:
ACM Transactions on Human-Robot Interaction (THRI) is a prestigious Gold Open Access journal that aspires to lead the field of human-robot interaction as a top-tier, peer-reviewed, interdisciplinary publication. The journal prioritizes articles that significantly contribute to the current state of the art, enhance overall knowledge, have a broad appeal, and are accessible to a diverse audience. Submissions are expected to meet a high scholarly standard, and authors are encouraged to ensure their research is well-presented, advancing the understanding of human-robot interaction, adding cutting-edge or general insights to the field, or challenging current perspectives in this research domain.
THRI warmly invites well-crafted paper submissions from a variety of disciplines, encompassing robotics, computer science, engineering, design, and the behavioral and social sciences. The scholarly articles published in THRI may cover a range of topics such as the nature of human interactions with robots and robotic technologies, methods to enhance or enable novel forms of interaction, and the societal or organizational impacts of these interactions. The editorial team is also keen on receiving proposals for special issues that focus on specific technical challenges or that apply human-robot interaction research to further areas like social computing, consumer behavior, health, and education.