Pub Date : 2021-08-08DOI: 10.1109/RO-MAN50785.2021.9515445
D. Doroftei, Tom De Vleeschauwer, S. Bue, Michaël Dewyn, Frik Vanderstraeten, G. D. Cubber
Autonomous systems have the potential to accomplish missions more quickly and effectively, while reducing risks to human operators and costs. However, since the use of autonomous systems is still relatively new, there are still a lot of challenges associated with trusting these systems. Without operators in direct control of all actions, there are significant concerns associated with endangering human lives or damaging equipment. For this reason, NATO has issued a challenge seeking to identify ways to improve decision-maker and operator trust when deploying autonomous systems, and de-risk their adoption. This paper presents the proposal of the winning solution to this NATO challenge. It approaches trust as a multi-dimensional concept, by incorporating the four dimensions of human-agent trust establishment in a digital twin context.
{"title":"Human-Agent Trust Evaluation in a Digital Twin Context","authors":"D. Doroftei, Tom De Vleeschauwer, S. Bue, Michaël Dewyn, Frik Vanderstraeten, G. D. Cubber","doi":"10.1109/RO-MAN50785.2021.9515445","DOIUrl":"https://doi.org/10.1109/RO-MAN50785.2021.9515445","url":null,"abstract":"Autonomous systems have the potential to accomplish missions more quickly and effectively, while reducing risks to human operators and costs. However, since the use of autonomous systems is still relatively new, there are still a lot of challenges associated with trusting these systems. Without operators in direct control of all actions, there are significant concerns associated with endangering human lives or damaging equipment. For this reason, NATO has issued a challenge seeking to identify ways to improve decision-maker and operator trust when deploying autonomous systems, and de-risk their adoption. This paper presents the proposal of the winning solution to this NATO challenge. It approaches trust as a multi-dimensional concept, by incorporating the four dimensions of human-agent trust establishment in a digital twin context.","PeriodicalId":6854,"journal":{"name":"2021 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN)","volume":"32 1","pages":"203-207"},"PeriodicalIF":0.0,"publicationDate":"2021-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86823187","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}
Pub Date : 2021-08-08DOI: 10.1109/RO-MAN50785.2021.9515388
Bart Bootsma, Giovanni Franzese, J. Kober
Teaching a robot how to navigate in a new environment only from the sensor input in an end-to-end fashion is still an open challenge with much attention from industry and academia. This paper proposes an algorithm with the name “Learning Interactively to Resolve Ambiguity” (LIRA) that tackles the problem of sensor policy fusion extending state- of-the-art methods by employing ambiguity awareness in the decision-making and solving it using active and interactive querying of the human expert. LIRA, in fact, employs Gaussian Processes for the estimation of the policy’s confidence and investigates the ambiguity due to the disagreement between the single sensor policies on the desired action to take. LIRA aims to make the teaching of new policies easier, learning from human demonstrations and correction.The experiments show that LIRA can be used for learning a sensor-fused policy from scratch or also leveraging the knowledge of existing single sensor policies. The experiments focus on the estimation of the human interventions required for teaching a successful navigation policy.
{"title":"Interactive Learning of Sensor Policy Fusion","authors":"Bart Bootsma, Giovanni Franzese, J. Kober","doi":"10.1109/RO-MAN50785.2021.9515388","DOIUrl":"https://doi.org/10.1109/RO-MAN50785.2021.9515388","url":null,"abstract":"Teaching a robot how to navigate in a new environment only from the sensor input in an end-to-end fashion is still an open challenge with much attention from industry and academia. This paper proposes an algorithm with the name “Learning Interactively to Resolve Ambiguity” (LIRA) that tackles the problem of sensor policy fusion extending state- of-the-art methods by employing ambiguity awareness in the decision-making and solving it using active and interactive querying of the human expert. LIRA, in fact, employs Gaussian Processes for the estimation of the policy’s confidence and investigates the ambiguity due to the disagreement between the single sensor policies on the desired action to take. LIRA aims to make the teaching of new policies easier, learning from human demonstrations and correction.The experiments show that LIRA can be used for learning a sensor-fused policy from scratch or also leveraging the knowledge of existing single sensor policies. The experiments focus on the estimation of the human interventions required for teaching a successful navigation policy.","PeriodicalId":6854,"journal":{"name":"2021 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN)","volume":"84 1","pages":"665-670"},"PeriodicalIF":0.0,"publicationDate":"2021-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87740676","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}
Pub Date : 2021-08-08DOI: 10.1109/RO-MAN50785.2021.9515472
Chatchalita Asavanant, H. Umemuro
Studies of personal space between human and robot have been growing. However, little is known about the effects of personal space violation by a robot. Expectation Violation Theory (EVT) explains how people respond to personal space invasion by another person, depending on if the person is perceived as rewarding or punishing. This study aims to extend EVT to HRI and to examine the effects of personal space violation using EVT as an analytical framework. A 2 × 5 within-subject experimental design was employed. The participants were approached by two robots with different reward value (rewarding and punishing) at varying distances (threat, near, norm, slightly far, and far distances). The participants were asked to rate the robots’ perceived warmth, competence, and comfort scores after each approach to evaluate the communication outcomes after the personal space violation occurred. The results suggested that approaching distances had influences on the communication outcomes. As predicted by EVT, how each distance affected the communication outcomes differ according on robot’s reward value. The findings indicated that EVT was partially successful in predicting the effects of personal space violations depending on the reward value and approaching distance of a robot. This study has provided a partial support that EVT can be applied to HRI and contributed to understanding the effects of personal space violation by a robot. When considering personal space in HRI, perceived reward value of the robot plays an important role as it can influence the effects of the personal space violation greatly.
{"title":"Personal Space Violation by a Robot: An Application of Expectation Violation Theory in Human-Robot Interaction","authors":"Chatchalita Asavanant, H. Umemuro","doi":"10.1109/RO-MAN50785.2021.9515472","DOIUrl":"https://doi.org/10.1109/RO-MAN50785.2021.9515472","url":null,"abstract":"Studies of personal space between human and robot have been growing. However, little is known about the effects of personal space violation by a robot. Expectation Violation Theory (EVT) explains how people respond to personal space invasion by another person, depending on if the person is perceived as rewarding or punishing. This study aims to extend EVT to HRI and to examine the effects of personal space violation using EVT as an analytical framework. A 2 × 5 within-subject experimental design was employed. The participants were approached by two robots with different reward value (rewarding and punishing) at varying distances (threat, near, norm, slightly far, and far distances). The participants were asked to rate the robots’ perceived warmth, competence, and comfort scores after each approach to evaluate the communication outcomes after the personal space violation occurred. The results suggested that approaching distances had influences on the communication outcomes. As predicted by EVT, how each distance affected the communication outcomes differ according on robot’s reward value. The findings indicated that EVT was partially successful in predicting the effects of personal space violations depending on the reward value and approaching distance of a robot. This study has provided a partial support that EVT can be applied to HRI and contributed to understanding the effects of personal space violation by a robot. When considering personal space in HRI, perceived reward value of the robot plays an important role as it can influence the effects of the personal space violation greatly.","PeriodicalId":6854,"journal":{"name":"2021 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN)","volume":"255 1","pages":"1181-1188"},"PeriodicalIF":0.0,"publicationDate":"2021-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86327858","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}
Pub Date : 2021-08-08DOI: 10.1109/RO-MAN50785.2021.9515468
Heikki Saul, Y. Hirata, Y. Weng
The users impairments are one of the most important factors for how a robotic mobility aid device is used. However, this has not been addressed in existing solutions. In this paper, we propose using information about the users’ disabilities and impairments to create a navigation prioritization layer for solving multi-robot navigation situations. To deal with the deep subjectivity inherent to assigning these priorities, we propose using human computation to create a navigation solution that will be aligned with humans’ personal value systems, increasing the perceived fairness and trustworthiness of the system. This paper covers the background, methodology, initial experiments and discusses the results, limitations, and future potential of the proposed approach.
{"title":"Use of Human Computation for Coordinating Robotic Mobility Aids Based on User Impairments *","authors":"Heikki Saul, Y. Hirata, Y. Weng","doi":"10.1109/RO-MAN50785.2021.9515468","DOIUrl":"https://doi.org/10.1109/RO-MAN50785.2021.9515468","url":null,"abstract":"The users impairments are one of the most important factors for how a robotic mobility aid device is used. However, this has not been addressed in existing solutions. In this paper, we propose using information about the users’ disabilities and impairments to create a navigation prioritization layer for solving multi-robot navigation situations. To deal with the deep subjectivity inherent to assigning these priorities, we propose using human computation to create a navigation solution that will be aligned with humans’ personal value systems, increasing the perceived fairness and trustworthiness of the system. This paper covers the background, methodology, initial experiments and discusses the results, limitations, and future potential of the proposed approach.","PeriodicalId":6854,"journal":{"name":"2021 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN)","volume":"52 1","pages":"858-864"},"PeriodicalIF":0.0,"publicationDate":"2021-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88970577","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}
Pub Date : 2021-08-08DOI: 10.1109/RO-MAN50785.2021.9515477
Jessica K. Barfield
This paper presents the results of research whose aim was to determine the type and amount of personal information individuals might disclose to robots designed with different visual appearances. The set of images viewed by participants consisted of two humanoid appearing robots and a female android. Further, a human image was used as a control for comparison purposes. For an individual to decide to disclose personal and potentially embarrassing information to a robot serving as a counselor, they must trust that the robot will safeguard their disclosures and be an empathetic listener. In this research 110 participants viewed four images and completed an online survey accessing their attitudes and decision on whether to self-disclose personal information to a robot counselor. Compared to the robot images, the results indicated a strong preference to disclose personal information to a human counselor regardless of the type of information. However, given the type of self-disclosure, the data also showed that participants would, to some extent, disclose to a friendly appearing robot and female android, and more so than to a robot judged to lack affect.
{"title":"Self-Disclosure of Personal Information, Robot Appearance, and Robot Trustworthiness","authors":"Jessica K. Barfield","doi":"10.1109/RO-MAN50785.2021.9515477","DOIUrl":"https://doi.org/10.1109/RO-MAN50785.2021.9515477","url":null,"abstract":"This paper presents the results of research whose aim was to determine the type and amount of personal information individuals might disclose to robots designed with different visual appearances. The set of images viewed by participants consisted of two humanoid appearing robots and a female android. Further, a human image was used as a control for comparison purposes. For an individual to decide to disclose personal and potentially embarrassing information to a robot serving as a counselor, they must trust that the robot will safeguard their disclosures and be an empathetic listener. In this research 110 participants viewed four images and completed an online survey accessing their attitudes and decision on whether to self-disclose personal information to a robot counselor. Compared to the robot images, the results indicated a strong preference to disclose personal information to a human counselor regardless of the type of information. However, given the type of self-disclosure, the data also showed that participants would, to some extent, disclose to a friendly appearing robot and female android, and more so than to a robot judged to lack affect.","PeriodicalId":6854,"journal":{"name":"2021 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN)","volume":"86 2 1","pages":"67-72"},"PeriodicalIF":0.0,"publicationDate":"2021-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88499979","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}
Pub Date : 2021-08-08DOI: 10.1109/RO-MAN50785.2021.9515354
Parastoo Baghaei Ravari, Ken Jen Lee, E. Law, D. Kulić
In this work, we designed a teachable robot that encourages a pair of students to discuss their thoughts and teaching decisions during the tutoring session. The robot adapts to the students’ talking activity and adjusts the frequency and type of encouragement. We hypothesize that the robot’s encouragement of group discussion can enhance the social engagement of group members, leading to improved learning and enjoyment. We ran a user study (n = 68), where a pair of participants (dyad) worked together to teach a humanoid robot about rocks and minerals. In the adaptive condition, the robot uses reinforcement learning to maximise interaction between the dyad members. Results show that the adaptive robot was successful in creating more dialogue between dyad members and in increasing task engagement, but did not affect learning or enjoyment. Over time, the adaptive robot was also able to encourage both members to contribute more equally to the conversation.
{"title":"Effects of an Adaptive Robot Encouraging Teamwork on Students’ Learning","authors":"Parastoo Baghaei Ravari, Ken Jen Lee, E. Law, D. Kulić","doi":"10.1109/RO-MAN50785.2021.9515354","DOIUrl":"https://doi.org/10.1109/RO-MAN50785.2021.9515354","url":null,"abstract":"In this work, we designed a teachable robot that encourages a pair of students to discuss their thoughts and teaching decisions during the tutoring session. The robot adapts to the students’ talking activity and adjusts the frequency and type of encouragement. We hypothesize that the robot’s encouragement of group discussion can enhance the social engagement of group members, leading to improved learning and enjoyment. We ran a user study (n = 68), where a pair of participants (dyad) worked together to teach a humanoid robot about rocks and minerals. In the adaptive condition, the robot uses reinforcement learning to maximise interaction between the dyad members. Results show that the adaptive robot was successful in creating more dialogue between dyad members and in increasing task engagement, but did not affect learning or enjoyment. Over time, the adaptive robot was also able to encourage both members to contribute more equally to the conversation.","PeriodicalId":6854,"journal":{"name":"2021 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN)","volume":"3 1","pages":"250-257"},"PeriodicalIF":0.0,"publicationDate":"2021-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84691968","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}
Pub Date : 2021-08-08DOI: 10.1109/RO-MAN50785.2021.9515429
N. Jecker
This paper argues for the possibility of e-friendship, a form of friendship between humans and silicon-based electronic agents. Section I introduces the topic. Section II defines "e-friendship." Sections III and IV identify qualities humans and silicon-based systems require for e-friendship. Section V defends the proposal against objections.
{"title":"My Friend, the Robot: An Argument for E-Friendship*","authors":"N. Jecker","doi":"10.1109/RO-MAN50785.2021.9515429","DOIUrl":"https://doi.org/10.1109/RO-MAN50785.2021.9515429","url":null,"abstract":"This paper argues for the possibility of e-friendship, a form of friendship between humans and silicon-based electronic agents. Section I introduces the topic. Section II defines \"e-friendship.\" Sections III and IV identify qualities humans and silicon-based systems require for e-friendship. Section V defends the proposal against objections.","PeriodicalId":6854,"journal":{"name":"2021 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN)","volume":"18 1","pages":"692-697"},"PeriodicalIF":0.0,"publicationDate":"2021-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84725255","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}
Pub Date : 2021-08-08DOI: 10.1109/RO-MAN50785.2021.9515499
Elena B. Sabinson, K. Green
Pandemic or not, many of us are spending more time indoors, apart from others and from nature. We report on user perceptions of "pheB," a non-anthropomorphic, bio-inspired, pneumatic-actuated robot surface aiming to help regulate our emotional states when inhabiting confined spaces, such as our homes. A survey (N = 50) tested perceived stress levels before and after performing guided breathing exercises under two conditions: led by the pheB prototype and a 2D vector graphic. We learned that perceived stress levels were significantly lower after performing the pheB led exercises. Comments from respondents who did not prefer pheB suggested a possible "Uncanny Valley" effect. The same survey elicited feedback on possible design features for pheB related to color, scale, orientation, and edge complexity. Beyond reporting on a soft robotic artifact of our own design, the research reported here offers an exemplar for conducting user studies online of novel robot designs, highlights user perceptions of bio-inspired robots in HRI research and considers biophilia and the uncanny valley for non-anthropomorphic robots supporting human-centered design applications.
{"title":"How do we feel? User Perceptions of a Soft Robot Surface for Regulating Human Emotion in Confined Living Spaces","authors":"Elena B. Sabinson, K. Green","doi":"10.1109/RO-MAN50785.2021.9515499","DOIUrl":"https://doi.org/10.1109/RO-MAN50785.2021.9515499","url":null,"abstract":"Pandemic or not, many of us are spending more time indoors, apart from others and from nature. We report on user perceptions of \"pheB,\" a non-anthropomorphic, bio-inspired, pneumatic-actuated robot surface aiming to help regulate our emotional states when inhabiting confined spaces, such as our homes. A survey (N = 50) tested perceived stress levels before and after performing guided breathing exercises under two conditions: led by the pheB prototype and a 2D vector graphic. We learned that perceived stress levels were significantly lower after performing the pheB led exercises. Comments from respondents who did not prefer pheB suggested a possible \"Uncanny Valley\" effect. The same survey elicited feedback on possible design features for pheB related to color, scale, orientation, and edge complexity. Beyond reporting on a soft robotic artifact of our own design, the research reported here offers an exemplar for conducting user studies online of novel robot designs, highlights user perceptions of bio-inspired robots in HRI research and considers biophilia and the uncanny valley for non-anthropomorphic robots supporting human-centered design applications.","PeriodicalId":6854,"journal":{"name":"2021 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN)","volume":"81 1","pages":"1153-1158"},"PeriodicalIF":0.0,"publicationDate":"2021-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86667561","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}
Pub Date : 2021-08-08DOI: 10.1109/RO-MAN50785.2021.9515439
Ala'aldin Hijaz, Jessica Korneder, W. Louie
Current studies have demonstrated that Socially Assistive Robots (SARs) delivering Applied Behavior Analysis (ABA) based interventions can teach individuals with Autism Spectrum Disorder (ASD) valuable social, emotional, communication and academic skills. These robot-mediated interventions (RMIs) are typically delivered via teleoperation, which places additional or similar workloads on therapists as administering interventions directly. The autonomous delivery of ABA therapies to individuals with ASD by a robot could significantly reduce workload and improve the usability as well as acceptance of this technology. However, pre-programming the autonomy of a SAR with a limited set of interventions is not sufficient for clinical practice due to the rapidly changing and different learning needs of individuals with ASD. In order to be applicable in clinical settings, therapists must be capable of customizing and personalizing interventions to the needs of each individual. Towards this goal, in this paper we present the initial development and deployment of a proof-of-concept Learning from Demonstration (LfD) system in-the-wild to learn the verbal behavior of therapists during the delivery of an ABA-based intervention to children with ASD. We also present preliminary data on the results of a policy trained on data collected from demonstrations provided during this in-the-wild deployment of our LfD system.
{"title":"In-the-Wild Learning from Demonstration for Therapies for Autism Spectrum Disorder","authors":"Ala'aldin Hijaz, Jessica Korneder, W. Louie","doi":"10.1109/RO-MAN50785.2021.9515439","DOIUrl":"https://doi.org/10.1109/RO-MAN50785.2021.9515439","url":null,"abstract":"Current studies have demonstrated that Socially Assistive Robots (SARs) delivering Applied Behavior Analysis (ABA) based interventions can teach individuals with Autism Spectrum Disorder (ASD) valuable social, emotional, communication and academic skills. These robot-mediated interventions (RMIs) are typically delivered via teleoperation, which places additional or similar workloads on therapists as administering interventions directly. The autonomous delivery of ABA therapies to individuals with ASD by a robot could significantly reduce workload and improve the usability as well as acceptance of this technology. However, pre-programming the autonomy of a SAR with a limited set of interventions is not sufficient for clinical practice due to the rapidly changing and different learning needs of individuals with ASD. In order to be applicable in clinical settings, therapists must be capable of customizing and personalizing interventions to the needs of each individual. Towards this goal, in this paper we present the initial development and deployment of a proof-of-concept Learning from Demonstration (LfD) system in-the-wild to learn the verbal behavior of therapists during the delivery of an ABA-based intervention to children with ASD. We also present preliminary data on the results of a policy trained on data collected from demonstrations provided during this in-the-wild deployment of our LfD system.","PeriodicalId":6854,"journal":{"name":"2021 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN)","volume":"117 1","pages":"1224-1229"},"PeriodicalIF":0.0,"publicationDate":"2021-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86798721","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}
Pub Date : 2021-08-08DOI: 10.1109/RO-MAN50785.2021.9515392
Antonis Sidiropoulos, Theodora Kastritsi, Dimitrios Papageorgiou, Z. Doulgeri
In this work, the problem of cooperative human-robot manipulation of an object with large inertia is addressed, considering the availability of a kinematically controlled industrial robot. In particular, a variable admittance control scheme is proposed, where the damping is adjusted based on the power transmitted from the human to the robot, with the aim of minimizing the energy injected by the human while also allowing her/him to have control over the task. The proposed approach is evaluated via a human-in-the-loop setup and compared to a generic variable damping state-of-the-art method. The proposed approach is shown to achieve significant reduction of the human’s effort and minimization of unintended overshoots and oscillations, which may deteriorate the user’s feeling of control over the task.
{"title":"A variable admittance controller for human-robot manipulation of large inertia objects","authors":"Antonis Sidiropoulos, Theodora Kastritsi, Dimitrios Papageorgiou, Z. Doulgeri","doi":"10.1109/RO-MAN50785.2021.9515392","DOIUrl":"https://doi.org/10.1109/RO-MAN50785.2021.9515392","url":null,"abstract":"In this work, the problem of cooperative human-robot manipulation of an object with large inertia is addressed, considering the availability of a kinematically controlled industrial robot. In particular, a variable admittance control scheme is proposed, where the damping is adjusted based on the power transmitted from the human to the robot, with the aim of minimizing the energy injected by the human while also allowing her/him to have control over the task. The proposed approach is evaluated via a human-in-the-loop setup and compared to a generic variable damping state-of-the-art method. The proposed approach is shown to achieve significant reduction of the human’s effort and minimization of unintended overshoots and oscillations, which may deteriorate the user’s feeling of control over the task.","PeriodicalId":6854,"journal":{"name":"2021 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN)","volume":"18 1","pages":"509-514"},"PeriodicalIF":0.0,"publicationDate":"2021-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76609751","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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