| 1. |
- Edström, Filip, 1991-, et al.
(författare)
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Robot causal discovery aided by human interaction
- 2023
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Ingår i: 2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN). - : IEEE. - 9798350336702 - 9798350336719 ; , s. 1731-1736
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Konferensbidrag (refereegranskat)abstract
- Causality is relatively unexplored in robotics even if it is highly relevant, in several respects. In this paper, we study how a robot’s causal understanding can be improved by allowing the robot to ask humans causal questions. We propose a general algorithm for selecting direct causal effects to ask about, given a partial causal representation (using partially directed acyclic graphs, PDAGs) obtained from observational data. We propose three versions of the algorithm inspired by different causal discovery techniques, such as constraint-based, score-based, and interventions. We evaluate the versions in a simulation study and our results show that asking causal questions improves the causal representation over all simulated scenarios. Further, the results show that asking causal questions based on PDAGs discovered from data provides a significant improvement compared to asking questions at random, and the version inspired by score-based techniques performs particularly well over all simulated experiments.
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| 2. |
- Kochenborger Duarte, Eduardo, 1994-, et al.
(författare)
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Trust in Robot Self-Defense : People Would Prefer a Competent, Tele-Operated Robot That Tries to Help∗
- 2023
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Ingår i: 2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN). - New York, NY : IEEE. - 9798350336702 - 9798350336719 ; , s. 2447-2453
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Konferensbidrag (refereegranskat)abstract
- Motivated by the expectation that robot presence at crime scenes will become increasingly prevalent, the question arises of how they can protect humans in their care or vicinity. The current paper delves into the concept of 'robot self-defense' and explores whether a robot should be tele-operated or autonomous, and how humans perceive imperfections in robot performance. To gain insight into how people feel, an online survey was conducted with 180 participants, who watched six videos of a robot defending a victim. The study provides insights into trust in human-robot interactions and sheds light on the complex dynamics involved in robot self-defense. The results indicate that people found a tele-operated robot to be more accepted, and that attempting to help but failing is more acceptable than just observing. © 2023 IEEE.
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| 3. |
- Rosén, Julia, et al.
(författare)
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Investigating NARS : Inconsistent Practice of Application and Reporting
- 2023
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Ingår i: Proceedings of the 2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN). - : IEEE. - 9798350336702 - 9798350336719 ; , s. 922-927
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Konferensbidrag (refereegranskat)abstract
- The Negative Attitude toward Robots Scale (NARS) is one of the most common questionnaires used in the studies of human-robot interaction (HRI). It was established in 2004, and has since then been used in several domains to measure attitudes, both as main results and as a potential confounding factor. To better understand this important tool of HRI research, we reviewed the HRI literature with a specific focus on practice and reporting related to NARS. We found that the use of NARS is being increasingly reported, and that there is a large variation in how NARS is applied. The reporting is, however, often not done in sufficient detail, meaning that NARS results are often difficult to interpret, and comparing between studies or performing meta-analyses are even more difficult. After providing an overview of the current state of NARS in HRI, we conclude with reflections and recommendations on the practices and reporting of NARS.
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| 4. |
- Schreiter, Tim, et al.
(författare)
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Advantages of Multimodal versus Verbal-Only Robot-to-Human Communication with an Anthropomorphic Robotic Mock Driver
- 2023
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Ingår i: 2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN). - : IEEE. - 9798350336702 - 9798350336719 ; , s. 293-300
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Konferensbidrag (refereegranskat)abstract
- Robots are increasingly used in shared environments with humans, making effective communication a necessity for successful human-robot interaction. In our work, we study a crucial component: active communication of robot intent. Here, we present an anthropomorphic solution where a humanoid robot communicates the intent of its host robot acting as an “Anthropomorphic Robotic Mock Driver” (ARMoD). We evaluate this approach in two experiments in which participants work alongside a mobile robot on various tasks, while the ARMoD communicates a need for human attention, when required, or gives instructions to collaborate on a joint task. The experiments feature two interaction styles of the ARMoD: a verbal-only mode using only speech and a multimodal mode, additionally including robotic gaze and pointing gestures to support communication and register intent in space. Our results show that the multimodal interaction style, including head movements and eye gaze as well as pointing gestures, leads to more natural fixation behavior. Participants naturally identified and fixated longer on the areas relevant for intent communication, and reacted faster to instructions in collaborative tasks. Our research further indicates that the ARMoD intent communication improves engagement and social interaction with mobile robots in workplace settings.
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| 5. |
- Schreiter, Tim, 1997-, et al.
(författare)
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Advantages of Multimodal versus Verbal-Only Robot-to-Human Communication with an Anthropomorphic Robotic Mock Driver
- 2023
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Ingår i: 2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN). - : IEEE. - 9798350336702 - 9798350336719 ; , s. 293-300
-
Konferensbidrag (refereegranskat)abstract
- Robots are increasingly used in shared environments with humans, making effective communication a necessity for successful human-robot interaction. In our work, we study a crucial component: active communication of robot intent. Here, we present an anthropomorphic solution where a humanoid robot communicates the intent of its host robot acting as an "Anthropomorphic Robotic Mock Driver" (ARMoD). We evaluate this approach in two experiments in which participants work alongside a mobile robot on various tasks, while the ARMoD communicates a need for human attention, when required, or gives instructions to collaborate on a joint task. The experiments feature two interaction styles of the ARMoD: a verbal-only mode using only speech and a multimodal mode, additionally including robotic gaze and pointing gestures to support communication and register intent in space. Our results show that the multimodal interaction style, including head movements and eye gaze as well as pointing gestures, leads to more natural fixation behavior. Participants naturally identified and fixated longer on the areas relevant for intent communication, and reacted faster to instructions in collaborative tasks. Our research further indicates that the ARMoD intent communication improves engagement and social interaction with mobile robots in workplace settings.
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| 6. |
- Torre, Ilaria, et al.
(författare)
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Can a gender-ambiguous voice reduce gender stereotypes in human-robot interactions?
- 2023
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Ingår i: Proceedings of the 2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN). - : IEEE. - 1944-9445. - 9798350336702 - 9798350336719 ; , s. 106-112
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Konferensbidrag (refereegranskat)abstract
- When deploying robots, its physical characteristics, role, and tasks are often fixed. Such factors can also be associated with gender stereotypes among humans, which then transfer to the robots. One factor that can induce gendering but is comparatively easy to change is the robot’s voice. Designing voice in a way that interferes with fixed factors might therefore be a way to reduce gender stereotypes in human-robot interaction contexts. To this end, we have conducted a video-based online study to investigate how factors that might inspire gendering of a robot interact. In particular, we investigated how giving the robot a gender-ambiguous voice can affect perception of the robot. We compared assessments (n=111) of videos in which a robot’s body presentation and occupation mis/matched with human gender stereotypes. We found evidence that a gender-ambiguous voice can reduce gendering of a robot endowed with stereotypically feminine or masculine attributes. The results can inform more just robot design while opening new questions regarding the phenomenon of robot gendering.
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| 7. |
- Galatolo, Alessio, et al.
(författare)
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Personality-Adapted Language Generation for Social Robots
- 2023
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Ingår i: 2023 32ND IEEE INTERNATIONAL CONFERENCE ON ROBOT AND HUMAN INTERACTIVE COMMUNICATION, RO-MAN. - : Institute of Electrical and Electronics Engineers (IEEE). - 9798350336702 ; , s. 1800-1807
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Konferensbidrag (refereegranskat)abstract
- Previous works in Human-Robot Interaction have demonstrated the positive potential benefit of designing social robots which express specific personalities. In this work, we focus specifically on the adaptation of language (as the choice of words, their order, etc.) following the extraversion trait. We look to investigate whether current language models could support more autonomous generations of such personality-expressive robot output. We examine the performance of two models with user studies evaluating (i) raw text output and (ii) text output when used within multi-modal speech from the Furhat robot. We find that the ability to successfully manipulate perceived extraversion sometimes varies across different dialogue topics. We were able to achieve correct manipulation of robot personality via our language adaptation, but our results suggest further work is necessary to improve the automation and generalisation abilities of these models.
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| 8. |
- Goo, Hideki Garcia, et al.
(författare)
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Victims and Observers : How Gender, Victimization Experience, and Biases Shape Perceptions of Robot Abuse
- 2023
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Ingår i: 2023 32ND IEEE INTERNATIONAL CONFERENCE ON ROBOT AND HUMAN INTERACTIVE COMMUNICATION, RO-MAN. - : Institute of Electrical and Electronics Engineers (IEEE). - 9798350336702 ; , s. 2439-2446
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Konferensbidrag (refereegranskat)abstract
- With the deployment of robots in public realms, researchers are seeing more and more cases of abusive disinhibition towards robots. Because robots embody gendered identities, poor navigation of antisocial dynamics may reinforce or exacerbate gender-based violence. Robots deployed in social settings must recognize and respond to abuse in a way that minimizes ethical risk. This will require designers to first understand the risk posed by abuse of robots, and how humans perceive robot-directed abuse. To that end, we conducted an exploratory study of reactions to a physically abusive interaction between a human perpetrator and a victimized agent. Given extensions of gendered biases to robotic agents, as well as associations between an agent's human likeness and the experiential capacity attributed to it, we quasi-manipulated the victim's humanness (via use of a human actor vs. NAO robot) and gendering (via inclusion of stereotypically masculine vs. feminine cues in their presentation) across four video-recorded reproductions of the interaction. Analysis of data from 417 participants, each of whom watched one of the four videos, indicates that the intensity of emotional distress felt by an observer is associated with their gender identification, previous experience with victimization, hostile sexism, and support for social stratification, as well as the victim's gendering.
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| 9. |
- Melsión, Gaspar Isaac, et al.
(författare)
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What's at Stake? : Robot explanations matter for high but not low-stake scenarios
- 2023
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Ingår i: 2023 32ND IEEE INTERNATIONAL CONFERENCE ON ROBOT AND HUMAN INTERACTIVE COMMUNICATION, RO-MAN. - : Institute of Electrical and Electronics Engineers (IEEE). - 9798350336702 ; , s. 2421-2426
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Konferensbidrag (refereegranskat)abstract
- Although the field of Explainable Artificial Intelligence (XAI) in Human-Robot Interaction is gathering increasing attention, how well different explanations compare across HRI scenarios is still not well understood. We conducted an exploratory online study with 335 participants analysing the interaction between type of explanation (counterfactual, feature-based, and no explanation), the stake of the scenario (high, low) and the application scenario (healthcare, industry). Participants viewed one of 12 different vignettes depicting a combination of these three factors and rated their system understanding and trust in the robot. Compared to no explanation, both counterfactual and feature-based explanations improved system understanding and performance trust (but not moral trust). Additionally, when no explanation was present, high-stake scenarios led to significantly worse performance trust and system understanding. These findings suggest that explanations can be used to calibrate users' perceptions of the robot in high-stake scenarios.
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| 10. |
- Romeo, Marta, et al.
(författare)
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Putting Robots in Context : Challenging the Influence of Voice and Empathic Behaviour on Trust
- 2023
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Ingår i: 2023 32ND IEEE INTERNATIONAL CONFERENCE ON ROBOT AND HUMAN INTERACTIVE COMMUNICATION, RO-MAN. - : Institute of Electrical and Electronics Engineers (IEEE). - 1944-9445. - 9798350336702 ; , s. 2045-2050
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Konferensbidrag (refereegranskat)abstract
- Trust is essential for social interactions, including those between humans and social artificial agents, such as robots. Several robot-related factors can contribute to the formation of trust. However, previous work has often treated trust as an absolute concept, whereas it is highly context-dependent, and it is possible that some robot-related features will influence trust in some contexts, but not in others. In this paper, we present the results of two video-based online studies aimed at investigating the role of robot voice and empathic behaviour on trust formation in a general context as well as in a task-specific context. We found that voice influences trust in the specific context, with no effect of voice or empathic behaviour in the general context. Thus, context mediated whether robot-related features play a role in people's trust formation towards robots.
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| 11. |
- Somashekarappa, Vidya, 1994, et al.
(författare)
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Neural Network Implementation of Gaze-Target Prediction for Human-Robot Interaction
- 2023
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Ingår i: IEEE International Workshop on Robot and Human Communication, RO-MAN. - 1944-9445 .- 1944-9437. - 9798350336702
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Konferensbidrag (refereegranskat)abstract
- Gaze cues, which initiate an action or behaviour, are necessary for a responsive and intuitive interaction. Using gaze to signal intentions or request an action during conversation is conventional. We propose a new approach to estimate gaze using a neural network architecture, while considering the dynamic patterns of real world gaze behaviour in natural interaction. The main goal is to provide foundation for robot/avatar to communicate with humans using natural multimodal-dialogue. Currently, robotic gaze systems are reactive in nature but our Gaze-Estimation framework can perform unified gaze detection, gaze-object prediction and object-landmark heatmap in a single scene, which paves the way for a more proactive approach. We generated 2.4M gaze predictions of various types of gaze in a more natural setting (GHIGaze). The predicted and categorised gaze data can be used to automate contextualized robotic gaze-tracking behaviour in interaction. We evaluate the performance on a manually-annotated data set and a publicly available gaze-follow dataset. Compared to previously reported methods our model performs better with the closest angular error to that of a human annotator. As future work, we propose an implementable gaze architecture for a social robot from Furhat robotics11https://furhatrobotics.com/
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| 12. |
- Winkle, Katie, et al.
(författare)
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Differing Care Giver and Care Receiver Perceptions of Robot Agency in an In-Home Socially Assistive Robot for Exercise Engagement
- 2023
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Ingår i: 2023 32ND IEEE INTERNATIONAL CONFERENCE ON ROBOT AND HUMAN INTERACTIVE COMMUNICATION, RO-MAN. - : Institute of Electrical and Electronics Engineers (IEEE). - 9798350336702 ; , s. 607-613
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Konferensbidrag (refereegranskat)abstract
- We present the results of an online, video-based experimental study investigating the impact of robot agency on perceptions of a socially assistive robot (SAR) shown supporting in-home care. We consider two key participant groups: care givers and care receivers. We did not find significant results regarding the impact of agency on overall participant perceptions of the SAR, but we did identify some differences in what these two participant groups might perceive as being best for themselves versus each other. Firstly, care givers perceived more potential benefit from the robot than care receivers did, challenging possible assumptions about who is set to gain most from deployment of these systems. Secondly, care receivers generally perceived the lower agency robot as being more beneficial for themselves, even as they ascribed the higher agency robot more potential to benefit care receivers.
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