Nialah Jenae Wilson-Small, D. Goedicke, Kirstin H. Petersen, Shiri Azenkot
Drones (micro unmanned aerial vehicles) are becoming more prevalent in applications that bring them into close human spaces. This is made possible in part by clear drone-to-human communication strategies. However, current auditory and visual communication methods only work with strict environmental settings. To continue expanding the possibilities for drones to be useful in human spaces, we explore ways to overcome these limitations through physical touch. We present a new application for drones--physical instructive feedback. To do this we designed three different physical interaction modes for a drone. We then conducted a user study (N=12) to answer fundamental questions of where and how people want to physically interact with drones, and what people naturally infer the physical touch is communicating. We then used these insights to conduct a second user study (N=14) to understand the best way for a drone to communicate instructions to a human in a movement task. We found that continuous physical feedback is both the preferred mode and is more effective at providing instruction than incremental feedback.
{"title":"A Drone Teacher: Designing Physical Human-Drone Interactions for Movement Instruction","authors":"Nialah Jenae Wilson-Small, D. Goedicke, Kirstin H. Petersen, Shiri Azenkot","doi":"10.1145/3568162.3576985","DOIUrl":"https://doi.org/10.1145/3568162.3576985","url":null,"abstract":"Drones (micro unmanned aerial vehicles) are becoming more prevalent in applications that bring them into close human spaces. This is made possible in part by clear drone-to-human communication strategies. However, current auditory and visual communication methods only work with strict environmental settings. To continue expanding the possibilities for drones to be useful in human spaces, we explore ways to overcome these limitations through physical touch. We present a new application for drones--physical instructive feedback. To do this we designed three different physical interaction modes for a drone. We then conducted a user study (N=12) to answer fundamental questions of where and how people want to physically interact with drones, and what people naturally infer the physical touch is communicating. We then used these insights to conduct a second user study (N=14) to understand the best way for a drone to communicate instructions to a human in a movement task. We found that continuous physical feedback is both the preferred mode and is more effective at providing instruction than incremental feedback.","PeriodicalId":36515,"journal":{"name":"ACM Transactions on Human-Robot Interaction","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76158836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study proposes a method to estimate pedestrian trust in an automated vehicle (AV) based on pedestrian behavior. It conducted experiments in a VR environment where an AV approached a crosswalk. Participants rated their trust in the AV at three levels before/while they crossed the road. The level can be estimated by deep learning using their skeletal coordinates, position, vehicle position, and speed during the past four seconds. The estimation accuracy was 61%.
{"title":"Trust Estimation for Autonomous Vehicles by Measuring Pedestrian Behavior in VR","authors":"Ryota Masuda, Shintaro Ono, T. Hiraoka, Y. Suda","doi":"10.1145/3568294.3580072","DOIUrl":"https://doi.org/10.1145/3568294.3580072","url":null,"abstract":"This study proposes a method to estimate pedestrian trust in an automated vehicle (AV) based on pedestrian behavior. It conducted experiments in a VR environment where an AV approached a crosswalk. Participants rated their trust in the AV at three levels before/while they crossed the road. The level can be estimated by deep learning using their skeletal coordinates, position, vehicle position, and speed during the past four seconds. The estimation accuracy was 61%.","PeriodicalId":36515,"journal":{"name":"ACM Transactions on Human-Robot Interaction","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75047130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
An often-forgotten group of people which is heavily affected by loneliness are young adults. The perceived social isolation often stems from attachment insecurities and social skill deficiencies. Since robots can function as social interaction partners who exert less social pressure and display less social complexity, they may pose a promising approach to alleviate this problematic situation. The goal would not be to replace human interaction partners, but to diminish acute loneliness and accompanying detrimental effects and to function as social skills coach and practice interaction partner. To explore the potential of this approach, a preregistered quantitative online study (N = 150) incorporating a video-based interaction with a social robot and qualitative elements was conducted. First results show that young adults report less state loneliness after interacting with the robot than before. Technically affine people evaluate the robot's sociability as well as the interaction with it more positively, people with a general negative attitude towards robots less positively. Furthermore, the more trait loneliness people report to experience, the less sociable they perceive the robot.
{"title":"Hey Robot, Can You Help Me Feel Less Lonely?: An Explorative Study to Examine the Potential of Using Social Robots to Alleviate Loneliness in Young Adults","authors":"Aike C. Horstmann","doi":"10.1145/3568294.3580135","DOIUrl":"https://doi.org/10.1145/3568294.3580135","url":null,"abstract":"An often-forgotten group of people which is heavily affected by loneliness are young adults. The perceived social isolation often stems from attachment insecurities and social skill deficiencies. Since robots can function as social interaction partners who exert less social pressure and display less social complexity, they may pose a promising approach to alleviate this problematic situation. The goal would not be to replace human interaction partners, but to diminish acute loneliness and accompanying detrimental effects and to function as social skills coach and practice interaction partner. To explore the potential of this approach, a preregistered quantitative online study (N = 150) incorporating a video-based interaction with a social robot and qualitative elements was conducted. First results show that young adults report less state loneliness after interacting with the robot than before. Technically affine people evaluate the robot's sociability as well as the interaction with it more positively, people with a general negative attitude towards robots less positively. Furthermore, the more trait loneliness people report to experience, the less sociable they perceive the robot.","PeriodicalId":36515,"journal":{"name":"ACM Transactions on Human-Robot Interaction","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75079642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sebastian Caballa, David Lizano, Manuel Aranda, Diego Zegarra
Injury burns are traumatic events, especially for children. The use of combined pharmacological and non-pharmacological strategies in hospitals favor emotional experiences. However, in Latin American hospitals, which have low budgets, it is not possible to hire therapeutic support personnel, such as clowns, due to the lack of available human resources. RoPi is a social robot created to assist hospitalized children's emotional support through its multicolor interchangeable pieces and its interactive functions.
{"title":"RoPi","authors":"Sebastian Caballa, David Lizano, Manuel Aranda, Diego Zegarra","doi":"10.1145/3568294.3580198","DOIUrl":"https://doi.org/10.1145/3568294.3580198","url":null,"abstract":"Injury burns are traumatic events, especially for children. The use of combined pharmacological and non-pharmacological strategies in hospitals favor emotional experiences. However, in Latin American hospitals, which have low budgets, it is not possible to hire therapeutic support personnel, such as clowns, due to the lack of available human resources. RoPi is a social robot created to assist hospitalized children's emotional support through its multicolor interchangeable pieces and its interactive functions.","PeriodicalId":36515,"journal":{"name":"ACM Transactions on Human-Robot Interaction","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77494799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Acceptance of robots is known to be directly influenced by perceptions and attitudes potential users have of them. Particularly, negative attitudes can prevent that the implementations of robots unlock their full potential and ultimately fail if negative attitudes are not addressed. We employed the popular Negative Attitude Towards Robots Scale (NARS) across four different studies to assess how different populations in Norway perceive robots. All four included exposure to at least a robot. However, the setup of each individual study was different from the others. We summarized the results across study and made comparisons between the different samples. We also analyzed the effect of gender and age on attitude towards robots as measured by the NARS. The results indicate that there are significant differences between samples and that females score significantly higher than males, thus having a less favorable opinion of robots and potentially avoiding interaction with them. We touch upon possible explanations and implications of our results and highlight the need for more research into this topic.
{"title":"Comparison of Attitudes Towards Robots of Different Population Samples in Norway","authors":"Marten Bloch, Alexandra Fernandes","doi":"10.1145/3568294.3580151","DOIUrl":"https://doi.org/10.1145/3568294.3580151","url":null,"abstract":"Acceptance of robots is known to be directly influenced by perceptions and attitudes potential users have of them. Particularly, negative attitudes can prevent that the implementations of robots unlock their full potential and ultimately fail if negative attitudes are not addressed. We employed the popular Negative Attitude Towards Robots Scale (NARS) across four different studies to assess how different populations in Norway perceive robots. All four included exposure to at least a robot. However, the setup of each individual study was different from the others. We summarized the results across study and made comparisons between the different samples. We also analyzed the effect of gender and age on attitude towards robots as measured by the NARS. The results indicate that there are significant differences between samples and that females score significantly higher than males, thus having a less favorable opinion of robots and potentially avoiding interaction with them. We touch upon possible explanations and implications of our results and highlight the need for more research into this topic.","PeriodicalId":36515,"journal":{"name":"ACM Transactions on Human-Robot Interaction","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77572879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Girish, Suchithra Selladurai, Vidhya Vidhya Sagar Murugan, Viboosithasri N S
Accessibility in transport hubs is indispensable for the upliftment of the social and economic spheres of persons with disabilities. Carla - a smart, autonomous personal assistant is proposed as an affordable solution to impart inclusivity in transport hubs. Carla can serve as a guide to the destination, an information kiosk and a luggage carrier. It is equipped with a rope guide and digital braille to serve people suffering from multi-sensory impairment. Carla can move to a modest push from the user - a novel feature introduced to enhance interaction. The system architecture and algorithm for autonomous navigation are also discussed. Finally, the interaction of Carla in a number of use cases are presented.
{"title":"Carla - Making Transport Hubs Accessible","authors":"A. Girish, Suchithra Selladurai, Vidhya Vidhya Sagar Murugan, Viboosithasri N S","doi":"10.1145/3568294.3580204","DOIUrl":"https://doi.org/10.1145/3568294.3580204","url":null,"abstract":"Accessibility in transport hubs is indispensable for the upliftment of the social and economic spheres of persons with disabilities. Carla - a smart, autonomous personal assistant is proposed as an affordable solution to impart inclusivity in transport hubs. Carla can serve as a guide to the destination, an information kiosk and a luggage carrier. It is equipped with a rope guide and digital braille to serve people suffering from multi-sensory impairment. Carla can move to a modest push from the user - a novel feature introduced to enhance interaction. The system architecture and algorithm for autonomous navigation are also discussed. Finally, the interaction of Carla in a number of use cases are presented.","PeriodicalId":36515,"journal":{"name":"ACM Transactions on Human-Robot Interaction","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78035947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Arora, Amit Arora, K. Sivakumar, John R. McIntyre
This ROB-I-LEARN research utilizes a versatile framework (e.g., Business Model Canvas or BMC) for robot design and curriculum development aimed at students diagnosed with autism spectrum disorder (ASD). Robotic interventions / human-robot interaction (HRI) field experiments with high school students were conducted as a recommendation or an outcome of the BMC framework and customer discovery interviews. These curriculum-related robotic interventions / interactive scenarios were designed to improve cognitive rehabilitation targeting students with ASD in high schools, thus enabling a higher quality learning environment that corresponds with students' learning requirements to prepare them for future learning and workforce environments.
{"title":"Robotic Interventions for Learning (ROB-I-LEARN): Examining Social Robotics for Learning Disabilities through Business Model Canvas","authors":"A. Arora, Amit Arora, K. Sivakumar, John R. McIntyre","doi":"10.1145/3568294.3580088","DOIUrl":"https://doi.org/10.1145/3568294.3580088","url":null,"abstract":"This ROB-I-LEARN research utilizes a versatile framework (e.g., Business Model Canvas or BMC) for robot design and curriculum development aimed at students diagnosed with autism spectrum disorder (ASD). Robotic interventions / human-robot interaction (HRI) field experiments with high school students were conducted as a recommendation or an outcome of the BMC framework and customer discovery interviews. These curriculum-related robotic interventions / interactive scenarios were designed to improve cognitive rehabilitation targeting students with ASD in high schools, thus enabling a higher quality learning environment that corresponds with students' learning requirements to prepare them for future learning and workforce environments.","PeriodicalId":36515,"journal":{"name":"ACM Transactions on Human-Robot Interaction","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79163684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Kubota, Rainee Pei, Ethan Sun, Dagoberto Cruz-Sandoval, Soyon Kim, L. Riek
Many robot-delivered health interventions aim to support people longitudinally at home to complement or replace in-clinic treatments. However, there is little guidance on how robots can support collaborative goal setting (CGS). CGS is the process in which a person works with a clinician to set and modify their goals for care; it can improve treatment adherence and efficacy. However, for home-deployed robots, clinicians will have limited availability to help set and modify goals over time, which necessitates that robots support CGS on their own. In this work, we explore how robots can facilitate CGS in the context of our robot CARMEN (Cognitively Assistive Robot for Motivation and Neurorehabilitation), which delivers neurorehabilitation to people with mild cognitive impairment (PwMCI). We co-designed robot behaviors for supporting CGS with clinical neuropsychologists and PwMCI, and prototyped them on CARMEN. We present feedback on how PwMCI envision these behaviors supporting goal progress and motivation during an intervention. We report insights on how to support this process with home-deployed robots and propose a framework to support HRI researchers interested in exploring this both in the context of cognitively assistive robots and beyond. This work supports designing and implementing CGS on robots, which will ultimately extend the efficacy of robot-delivered health interventions.
{"title":"Get SMART: Collaborative Goal Setting with Cognitively Assistive Robots","authors":"A. Kubota, Rainee Pei, Ethan Sun, Dagoberto Cruz-Sandoval, Soyon Kim, L. Riek","doi":"10.1145/3568162.3576993","DOIUrl":"https://doi.org/10.1145/3568162.3576993","url":null,"abstract":"Many robot-delivered health interventions aim to support people longitudinally at home to complement or replace in-clinic treatments. However, there is little guidance on how robots can support collaborative goal setting (CGS). CGS is the process in which a person works with a clinician to set and modify their goals for care; it can improve treatment adherence and efficacy. However, for home-deployed robots, clinicians will have limited availability to help set and modify goals over time, which necessitates that robots support CGS on their own. In this work, we explore how robots can facilitate CGS in the context of our robot CARMEN (Cognitively Assistive Robot for Motivation and Neurorehabilitation), which delivers neurorehabilitation to people with mild cognitive impairment (PwMCI). We co-designed robot behaviors for supporting CGS with clinical neuropsychologists and PwMCI, and prototyped them on CARMEN. We present feedback on how PwMCI envision these behaviors supporting goal progress and motivation during an intervention. We report insights on how to support this process with home-deployed robots and propose a framework to support HRI researchers interested in exploring this both in the context of cognitively assistive robots and beyond. This work supports designing and implementing CGS on robots, which will ultimately extend the efficacy of robot-delivered health interventions.","PeriodicalId":36515,"journal":{"name":"ACM Transactions on Human-Robot Interaction","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81563767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The use of social robots as a tool for language learning has been studied quite extensively recently. Although their effectiveness and comparison with other technologies are well studied, the effects of the robot's appearance and the interaction setting have received less attention. As educational robots are envisioned to appear in household or school environments, it is important to investigate how their designed persona or interaction dynamics affect learning outcomes. In such environments, children may do the activities together or alone or perform them in the presence of an adult or another child. In this regard, we have identified two novel factors to investigate: the robot's perceived age (adult or child) and the number of learners interacting with the robot simultaneously (one or two). We designed an incidental word learning card game with the Furhat robot and ran a between-subject experiment with 75 middle school participants. We investigated the interactions and effects of children's word learning outcomes, speech activity, and perception of the robot's role. The results show that children who played alone with the robot had better word retention and anthropomorphized the robot more, compared to those who played in pairs. Furthermore, unlike previous findings from human-human interactions, children did not show different behaviors in the presence of a robot designed as an adult or a child. We discuss these factors in detail and make a novel contribution to the direct comparison of collaborative versus individual learning and the new concept of the robot's age.
{"title":"I Learn Better Alone! Collaborative and Individual Word Learning With a Child and Adult Robot","authors":"Alireza M. Kamelabad, G. Skantze","doi":"10.1145/3568162.3577004","DOIUrl":"https://doi.org/10.1145/3568162.3577004","url":null,"abstract":"The use of social robots as a tool for language learning has been studied quite extensively recently. Although their effectiveness and comparison with other technologies are well studied, the effects of the robot's appearance and the interaction setting have received less attention. As educational robots are envisioned to appear in household or school environments, it is important to investigate how their designed persona or interaction dynamics affect learning outcomes. In such environments, children may do the activities together or alone or perform them in the presence of an adult or another child. In this regard, we have identified two novel factors to investigate: the robot's perceived age (adult or child) and the number of learners interacting with the robot simultaneously (one or two). We designed an incidental word learning card game with the Furhat robot and ran a between-subject experiment with 75 middle school participants. We investigated the interactions and effects of children's word learning outcomes, speech activity, and perception of the robot's role. The results show that children who played alone with the robot had better word retention and anthropomorphized the robot more, compared to those who played in pairs. Furthermore, unlike previous findings from human-human interactions, children did not show different behaviors in the presence of a robot designed as an adult or a child. We discuss these factors in detail and make a novel contribution to the direct comparison of collaborative versus individual learning and the new concept of the robot's age.","PeriodicalId":36515,"journal":{"name":"ACM Transactions on Human-Robot Interaction","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81923008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Human-robot interaction has the power to influence human norms and culture. While there is potential benefit in using this power to create positive social change, so too is there risk in merely reinforcing existing social biases which uphold systems of oppression. As the most salient forms of oppression arise along lines of social identity, it stands to reason that we must take utmost care in leveraging human-like identity cues when designing social robots and other agentic embodiments. Yet, the understanding of how to do this is not well-developed. Towards forming an ethics of robot identity, we begin by surveying the state of thought on the topic in human-robot interaction. We do this by conducting a structured review of HRI conference proceedings analyzed from a feminist, intersectional perspective. Our initial findings suggest that existing literature has not fully engaged with intersectionality, embodies an alarming pathologization of neurodivergence, and almost wholly neglects the examination of race.
{"title":"Examining the State of Robot Identity","authors":"Lux Miranda, Ginevra Castellano, Katie Winkle","doi":"10.1145/3568294.3580168","DOIUrl":"https://doi.org/10.1145/3568294.3580168","url":null,"abstract":"Human-robot interaction has the power to influence human norms and culture. While there is potential benefit in using this power to create positive social change, so too is there risk in merely reinforcing existing social biases which uphold systems of oppression. As the most salient forms of oppression arise along lines of social identity, it stands to reason that we must take utmost care in leveraging human-like identity cues when designing social robots and other agentic embodiments. Yet, the understanding of how to do this is not well-developed. Towards forming an ethics of robot identity, we begin by surveying the state of thought on the topic in human-robot interaction. We do this by conducting a structured review of HRI conference proceedings analyzed from a feminist, intersectional perspective. Our initial findings suggest that existing literature has not fully engaged with intersectionality, embodies an alarming pathologization of neurodivergence, and almost wholly neglects the examination of race.","PeriodicalId":36515,"journal":{"name":"ACM Transactions on Human-Robot Interaction","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85083642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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