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Rosén, J., Lindblom, J., Lamb, M. & Billing, E. (2024). Previous Experience Matters: An in-Person Investigation of Expectations in Human–Robot Interaction. International Journal of Social Robotics
Open this publication in new window or tab >>Previous Experience Matters: An in-Person Investigation of Expectations in Human–Robot Interaction
2024 (English)In: International Journal of Social Robotics, ISSN 1875-4791, E-ISSN 1875-4805Article in journal (Refereed) Epub ahead of print
Abstract [en]

The human–robot interaction (HRI) field goes beyond the mere technical aspects of developing robots, often investigating how humans perceive robots. Human perceptions and behavior are determined, in part, by expectations. Given the impact of expectations on behavior, it is important to understand what expectations individuals bring into HRI settings and how those expectations may affect their interactions with the robot over time. For many people, social robots are not a common part of their experiences, thus any expectations they have of social robots are likely shaped by other sources. As a result, individual expectations coming into HRI settings may be highly variable. Although there has been some recent interest in expectations within the field, there is an overall lack of empirical investigation into its impacts on HRI, especially in-person robot interactions. To this end, a within-subject in-person study () was performed where participants were instructed to engage in open conversation with the social robot Pepper during two 2.5 min sessions. The robot was equipped with a custom dialogue system based on the GPT-3 large language model, allowing autonomous responses to verbal input. Participants’ affective changes towards the robot were assessed using three questionnaires, NARS, RAS, commonly used in HRI studies, and Closeness, based on the IOS scale. In addition to the three standard questionnaires, a custom question was administered to capture participants’ views on robot capabilities. All measures were collected three times, before the interaction with the robot, after the first interaction with the robot, and after the second interaction with the robot. Results revealed that participants to large degrees stayed with the expectations they had coming into the study, and in contrast to our hypothesis, none of the measured scales moved towards a common mean. Moreover, previous experience with robots was revealed to be a major factor of how participants experienced the robot in the study. These results could be interpreted as implying that expectations of robots are to large degrees decided before interactions with the robot, and that these expectations do not necessarily change as a result of the interaction. Results reveal a strong connection to how expectations are studied in social psychology and human-human interaction, underpinning its relevance for HRI research.

Place, publisher, year, edition, pages
Springer Nature, 2024
Keywords
Expectations, Previous experience, Social robot, Human–robot interaction, Experiment, Expectation gap, Pepper, GPT, Large language models
National Category
Robotics Human Computer Interaction Social Psychology
Research subject
Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-23641 (URN)10.1007/s12369-024-01107-3 (DOI)
Funder
University of Skövde
Note

CC BY 4.0 DEED

Published: 29 February 2024

Open access funding provided by University of Skövde.

Available from: 2024-02-29 Created: 2024-02-29 Last updated: 2024-02-29
Rosén, J., Lagerstedt, E. & Lamb, M. (2023). Investigating NARS: Inconsistent Practice of Application and Reporting. In: Proceedings of the 2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN): . Paper presented at IEEE International Workshop on Robot and Human Communication (ROMAN), August 28-31, 2023, Paradise Hotel, Busan, Korea (pp. 922-927). IEEE
Open this publication in new window or tab >>Investigating NARS: Inconsistent Practice of Application and Reporting
2023 (English)In: Proceedings of the 2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), IEEE, 2023, p. 922-927Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
IEEE, 2023
Series
IEEE International Symposium on Robot and Human Interactive Communication proceedings, ISSN 1944-9445, E-ISSN 1944-9437
National Category
Robotics Human Aspects of ICT Interaction Technologies
Research subject
Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-23359 (URN)10.1109/RO-MAN57019.2023.10309650 (DOI)001108678600106 ()979-8-3503-3670-2 (ISBN)979-8-3503-3671-9 (ISBN)
Conference
IEEE International Workshop on Robot and Human Communication (ROMAN), August 28-31, 2023, Paradise Hotel, Busan, Korea
Available from: 2023-11-14 Created: 2023-11-14 Last updated: 2024-01-05Bibliographically approved
Billing, E., Rosén, J. & Lamb, M. (2023). Language Models for Human-Robot Interaction. In: HRI '23: Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction. Paper presented at ACM/IEEE International Conference on Human-Robot Interaction, March 13–16, 2023, Stockholm, Sweden (pp. 905-906). ACM Digital Library
Open this publication in new window or tab >>Language Models for Human-Robot Interaction
2023 (English)In: HRI '23: Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction, ACM Digital Library, 2023, p. 905-906Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

Recent advances in large scale language models have significantly changed the landscape of automatic dialogue systems and chatbots. We believe that these models also have a great potential for changing the way we interact with robots. Here, we present the first integration of the OpenAI GPT-3 language model for the Aldebaran Pepper and Nao robots. The present work transforms the text-based API of GPT-3 into an open verbal dialogue with the robots. The system will be presented live during the HRI2023 conference and the source code of this integration is shared with the hope that it will serve the community in designing and evaluating new dialogue systems for robots.

Place, publisher, year, edition, pages
ACM Digital Library, 2023
National Category
Language Technology (Computational Linguistics) Computer Vision and Robotics (Autonomous Systems)
Research subject
Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-22328 (URN)10.1145/3568294.3580040 (DOI)001054975700198 ()2-s2.0-85150449271 (Scopus ID)978-1-4503-9970-8 (ISBN)
Conference
ACM/IEEE International Conference on Human-Robot Interaction, March 13–16, 2023, Stockholm, Sweden
Note

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).

Available from: 2023-03-17 Created: 2023-03-17 Last updated: 2023-10-13Bibliographically approved
Almirón Santa-Bárbara, R., García Rivera, F., Lamb, M., Víquez Da-Silva, R. & Gutiérrez Bedmar, M. (2023). New technologies for the classification of proximal humeral fractures: Comparison between Virtual Reality and 3D printed models—a randomised controlled trial. Virtual Reality, 27(3), 1623-1634
Open this publication in new window or tab >>New technologies for the classification of proximal humeral fractures: Comparison between Virtual Reality and 3D printed models—a randomised controlled trial
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2023 (English)In: Virtual Reality, ISSN 1359-4338, E-ISSN 1434-9957, Vol. 27, no 3, p. 1623-1634Article in journal (Refereed) Published
Abstract [en]

Correct classification of fractures according to their patterns is critical for developing a treatment plan in orthopaedic surgery. Unfortunately, for proximal humeral fractures (PHF), methods for proper classification have remained a jigsaw puzzle that has not yet been fully solved despite numerous proposed classifications and diagnostic methods. Recently, many studies have suggested that three-dimensional printed models (3DPM) can improve the interobserver agreement on PHF classifications. Moreover, Virtual Reality (VR) has not been properly studied for classification of shoulder injuries. The current study investigates the PHF classification accuracy relative to an expert committee when using either 3DPM or equivalent models displayed in VR among 36 orthopaedic surgery residents from different hospitals. We designed a multicentric randomised controlled trial in which we created two groups: a group exposed to a total of 34 3DPM and another exposed to VR equivalents. Association between classification accuracy and group assignment (VR/3DPM) was assessed using mixed effects logistic regression models. The results showed VR can be considered a non-inferior technology for classifying PHF when compared to 3DPM. Moreover, VR may be preferable when considering possible time and resource savings along with potential uses of VR for presurgical planning in orthopaedics. 

Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH, 2023
Keywords
Fracture, Orthopedics, Regression analysis, Surgery, Virtual reality, Classification accuracy, Exposed to, Humeral fractures, Interobserver agreement, Orthopaedic surgery, Proximal humeral fracture, Randomized controlled trial, Shoulder surgery planning, Surgery planning, Three-dimensional printed model, 3D printing, Three-dimensional printed models
National Category
Orthopaedics Surgery Human Computer Interaction
Research subject
Interaction Lab (ILAB); User Centred Product Design
Identifiers
urn:nbn:se:his:diva-22269 (URN)10.1007/s10055-023-00757-4 (DOI)000926409600001 ()2-s2.0-85147386442 (Scopus ID)
Note

CC BY 4.0

© 2023, The Author(s)

Published: 04 February 2023

Funding for open access publishing: Universidad Málaga/CBUA.

Available from: 2023-02-16 Created: 2023-02-16 Last updated: 2023-09-22Bibliographically approved
Perez Luque, E., Brolin, E., Högberg, D. & Lamb, M. (2022). Challenges for the Consideration of Ergonomics in Product Development in the Swedish Automotive Industry – An Interview Study. In: DESIGN2022: . Paper presented at DESIGN2022, 17th International Design Conference, May, 23-26, 2022, Croatia (pp. 2165-2174). Cambridge University Press, 2
Open this publication in new window or tab >>Challenges for the Consideration of Ergonomics in Product Development in the Swedish Automotive Industry – An Interview Study
2022 (English)In: DESIGN2022, Cambridge University Press, 2022, Vol. 2, p. 2165-2174Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents an interview study aiming to understand the state of the art of how ergonomics designers work in the vehicle development process within the Swedish automotive industry. Ten ergonomic designers from seven different companies participated in the interview study. Results report the ergonomics designers' objectives, workflow, tools, challenges, and ideal work performance tool. We identify four main gaps and research directions that can enhance the current challenges: human behavior predictions, simulation tool usability, ergonomics evaluations, and integration between systems.

Place, publisher, year, edition, pages
Cambridge University Press, 2022
Series
Proceedings of the Design Society, E-ISSN 2732-527X ; Volume 2 - May 2022
Keywords
vehicle, ergonomics, human-centred design, simulation-based design, digital human modelling
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design; Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-22133 (URN)10.1017/pds.2022.219 (DOI)2-s2.0-85131373032 (Scopus ID)
Conference
DESIGN2022, 17th International Design Conference, May, 23-26, 2022, Croatia
Funder
Knowledge Foundation
Note

estela.perez.luque@his.se

This work has been made possible with the support from Knowledge Foundation in the project ADOPTIVE-Automated Design and Optimisation of Vehicle Ergonomics and participating organizations. This support is gratefully acknowledged.

Available from: 2022-12-16 Created: 2022-12-16 Last updated: 2023-01-17Bibliographically approved
Hanson, L., Högberg, D., Brolin, E., Billing, E., Iriondo Pascual, A. & Lamb, M. (2022). Current Trends in Research and Application of Digital Human Modeling. In: Nancy L. Black; W. Patrick Neumann; Ian Noy (Ed.), Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021): Volume V: Methods & Approaches. Paper presented at 21st Congress of the International Ergonomics Association (IEA 2021), 13-18 June (pp. 358-366). Cham: Springer
Open this publication in new window or tab >>Current Trends in Research and Application of Digital Human Modeling
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2022 (English)In: Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021): Volume V: Methods & Approaches / [ed] Nancy L. Black; W. Patrick Neumann; Ian Noy, Cham: Springer, 2022, p. 358-366Conference paper, Published paper (Refereed)
Abstract [en]

The paper reports an investigation conducted during the DHM2020 Symposium regarding current trends in research and application of DHM in academia, software development, and industry. The results show that virtual reality (VR), augmented reality (AR), and digital twin are major current trends. Furthermore, results show that human diversity is considered in DHM using established methods. Results also show a shift from the assessment of static postures to assessment of sequences of actions, combined with a focus mainly on human well-being and only partly on system performance. Motion capture and motion algorithms are alternative technologies introduced to facilitate and improve DHM simulations. Results from the DHM simulations are mainly presented through pictures or animations.

Place, publisher, year, edition, pages
Cham: Springer, 2022
Series
Lecture Notes in Networks and Systems, ISSN 2367-3370, E-ISSN 2367-3389 ; 223
Keywords
Digital Human Modeling, Trends, Research, Development, Application
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design; Interaction Lab (ILAB); VF-KDO
Identifiers
urn:nbn:se:his:diva-19959 (URN)10.1007/978-3-030-74614-8_44 (DOI)2-s2.0-85111461730 (Scopus ID)978-3-030-74613-1 (ISBN)978-3-030-74614-8 (ISBN)
Conference
21st Congress of the International Ergonomics Association (IEA 2021), 13-18 June
Funder
Knowledge Foundation, 20180167Vinnova, 2018-05026Knowledge Foundation, 20200003
Note

© 2022

Available from: 2021-06-22 Created: 2021-06-22 Last updated: 2023-08-16Bibliographically approved
Garcia Rivera, F., Högberg, D., Lamb, M. & Perez Luque, E. (2022). DHM supported assessment of the effects of using an exoskeleton during work. International Journal of Human Factors Modelling and Simulation, 7(3/4), 231-246
Open this publication in new window or tab >>DHM supported assessment of the effects of using an exoskeleton during work
2022 (English)In: International Journal of Human Factors Modelling and Simulation, ISSN 1742-5549, Vol. 7, no 3/4, p. 231-246Article in journal (Refereed) Published
Abstract [en]

Recently, exoskeletons have been gaining popularity in many industries, primarily for supporting manual assembly tasks. Due to the relative novelty of exoskeleton technologies, knowledge about the consequences of using these devices at workstations is still developing. Digital human modelling (DHM) and ergonomic evaluation tools may be of particular use in this context. However, there are no standard integrations of DHM and ergonomic assessment tools for assessing exoskeletons. This paper proposes a general method for evaluating the ergonomic effects of introducing an exoskeleton in a production context using DHM simulation tools combined with a modified existing ergonomic assessment framework. More specifically, we propose adapting the Assembly Specific Force Atlas tool to evaluate exoskeletons by increasing the risk level threshold proportionally to the amount of torque that the exoskeleton reduces in the glenohumeral joint. We illustrate this adaptation in a DHM tool. We believe the proposed methodology and the corresponding workflow can be helpful for decision-makers and stakeholders when considering implementing exoskeletons in a production environment.

Place, publisher, year, edition, pages
Geneva: InderScience Publishers, 2022
Keywords
digital human modelling, DHM, assessment, ergonomics, exoskeleton, Assembly Specific Force Atlas, ASFA
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design; INF202 Virtual Ergonomics; Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-21703 (URN)10.1504/ijhfms.2021.10048920 (DOI)
Funder
Vinnova, 2018-05026Knowledge Foundation, 20180167
Available from: 2022-08-22 Created: 2022-08-22 Last updated: 2022-10-17Bibliographically approved
Lamb, M., Brundin, M., Perez Luque, E. & Billing, E. (2022). Eye-Tracking Beyond Peripersonal Space in Virtual Reality: Validation and Best Practices. Frontiers in Virtual Reality, 3, Article ID 864653.
Open this publication in new window or tab >>Eye-Tracking Beyond Peripersonal Space in Virtual Reality: Validation and Best Practices
2022 (English)In: Frontiers in Virtual Reality, E-ISSN 2673-4192, Vol. 3, article id 864653Article in journal (Refereed) Published
Abstract [en]

Recent developments in commercial virtual reality (VR) hardware with embedded eye-tracking create tremendous opportunities for human subjects researchers. Accessible eye-tracking in VR opens new opportunities for highly controlled experimental setups in which participants can engage novel 3D digital environments. However, because VR embedded eye-tracking differs from the majority of historical eye-tracking research, in both providing for relatively unconstrained movement and stimulus presentation distances, there is a need for greater discussion around methods for implementation and validation of VR based eye-tracking tools. The aim of this paper is to provide a practical introduction to the challenges of, and methods for, 3D gaze-tracking in VR with a focus on best practices for results validation and reporting. Specifically, first, we identify and define challenges and methods for collecting and analyzing 3D eye-tracking data in VR. Then, we introduce a validation pilot study with a focus on factors related to 3D gaze tracking. The pilot study provides both a reference data point for a common commercial hardware/software platform (HTC Vive Pro Eye) and illustrates the proposed methods. One outcome of this study was the observation that accuracy and precision of collected data may depend on stimulus distance, which has consequences for studies where stimuli is presented on varying distances. We also conclude that vergence is a potentially problematic basis for estimating gaze depth in VR and should be used with caution as the field move towards a more established method for 3D eye-tracking.

Place, publisher, year, edition, pages
Frontiers Media S.A., 2022
Keywords
eye tracking, virtual reality, gaze depth, vergence, validation
National Category
Computer Sciences Human Computer Interaction Interaction Technologies
Research subject
Interaction Lab (ILAB); User Centred Product Design
Identifiers
urn:nbn:se:his:diva-21062 (URN)10.3389/frvir.2022.864653 (DOI)001023339600001 ()2-s2.0-85138010016 (Scopus ID)
Funder
Knowledge Foundation
Note

CC BY 4.0

Correspondence: Maurice Lamb Maurice.Lamb@his.se

published: 08 April 2022

The raw data supporting the conclusions of this article will bemade available by the authors, without undue reservation. The software used for data collection in this project can be found at https://doi.org/10.5281/zenodo.6368107.

Funding of this project was provided through the Knowledge Foundation as a part of both the Recruitment and Strategic Knowledge Reinforcement initiative and within the Synergy Virtual Ergonomics (SVE) project (#20180167).

We want to thank the Knowledge Foundation and the associated INFINIT research environment at the University of Skövde for support through funding of both the Recruitment and Strategic Knowledge Reinforcement initiative and within the Synergy Virtual Ergonomics (SVE) project. This support is gratefully acknowledged.

Available from: 2022-04-14 Created: 2022-04-14 Last updated: 2023-08-23Bibliographically approved
Lamb, M., Seunghun, L., Billing, E., Högberg, D. & Yang, J. (2022). Forward and Backward Reaching Inverse Kinematics (FABRIK) solver for DHM: A pilot study. In: Proceedings of the 7th International Digital Human Modeling Symposium (DHM 2022), August 29–30, 2022, Iowa City, Iowa, USA: . Paper presented at 7th International Digital Human Modeling Symposium (DHM 2022), August 29–30, 2022, Iowa City, Iowa, USA. The conference was followed by the Iowa Virtual Human Summit 2022. (pp. 1-11). University of Iowa Press, 7, Article ID 26.
Open this publication in new window or tab >>Forward and Backward Reaching Inverse Kinematics (FABRIK) solver for DHM: A pilot study
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2022 (English)In: Proceedings of the 7th International Digital Human Modeling Symposium (DHM 2022), August 29–30, 2022, Iowa City, Iowa, USA, University of Iowa Press, 2022, Vol. 7, p. 1-11, article id 26Conference paper, Published paper (Refereed)
Abstract [en]

Posture/motion prediction is the basis of the human motion simulations that make up the core of many digital human modeling (DHM) tools and methods. With the goal of producing realistic postures and motions, a common element of posture/motion prediction methods involves applying some set of constraints to biomechanical models of humans on the positions and orientations of specified body parts. While many formulations of biomechanical constraints may produce valid predictions, they must overcome the challenges posed by the highly redundant nature of human biomechanical systems. DHM researchers and developers typically focus on optimization formulations to facilitate the identification and selection of valid solutions. While these approaches produce optimal behavior according to some, e.g., ergonomic, optimization criteria, these solutions require considerable computational power and appear vastly different from how humans produce motion. In this paper, we take a different approach and consider the Forward and Backward Reaching Inverse Kinematics (FABRIK) solver developed in the context of computer graphics for rigged character animation. This approach identifies postures quickly and efficiently, often requiring a fraction of the computation time involved in optimization-based methods. Critically, the FABRIK solver identifies posture predictions based on a lightweight heuristic approach. Specifically, the solver works in joint position space and identifies solutions according to a minimal joint displacement principle. We apply the FABRIK solver to a seven-degree of freedom human arm model during a reaching task from an initial to an end target location, fixing the shoulder position and providing the end effector (index fingertip) position and orientation from each frame of the motion capture data. In this preliminary study, predicted postures are compared to experimental data from a single human subject. Overall the predicted postures were very near the recorded data, with an average RMSE of 1.67°. Although more validation is necessary, we believe that the FABRIK solver has great potential for producing realistic human posture/motion in real-time, with applications in the area of DHM.

Place, publisher, year, edition, pages
University of Iowa Press, 2022
Keywords
Inverse Kinematics, Posture Prediction, IK validation, FABRIK
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design; Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-21830 (URN)10.17077/dhm.31772 (DOI)978-0-9840378-4-1 (ISBN)
Conference
7th International Digital Human Modeling Symposium (DHM 2022), August 29–30, 2022, Iowa City, Iowa, USA. The conference was followed by the Iowa Virtual Human Summit 2022.
Note

Copyright © 2022 the author(s) 

Available from: 2022-09-20 Created: 2022-09-20 Last updated: 2022-10-17Bibliographically approved
Babajanyan, D., Patil, G., Lamb, M., Kallen, R. W. & Richardson, M. J. (2022). I Know Your Next Move: Action Decisions in Dyadic Pick and Place Tasks. In: J. Culbertson; A. Perfors; H. Rabagliati; V. Ramenzoni (Ed.), Proceedings of the 44th Annual Conference of the Cognitive Science Society: . Paper presented at 44th Annual Meeting of the Cognitive Science Society: Cognitive Diversity, CogSci 2022, Toronto 27 July 2022 through 30 July 2022, Code 185866 (pp. 563-570). Cognitive Science Society, Inc.
Open this publication in new window or tab >>I Know Your Next Move: Action Decisions in Dyadic Pick and Place Tasks
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2022 (English)In: Proceedings of the 44th Annual Conference of the Cognitive Science Society / [ed] J. Culbertson; A. Perfors; H. Rabagliati; V. Ramenzoni, Cognitive Science Society, Inc., 2022, p. 563-570Conference paper, Published paper (Refereed)
Abstract [en]

Joint pick and place tasks occur in many interpersonal scenarios, such as when two people pick up and pass dishes. Previous studies have demonstrated that low-dimensional models can accurately capture the dynamics of pick and place motor behaviors in a controlled 2D environment. The current study models the dynamics of pick-up and pass decisions within a less restrictive virtual reality mediated 3D joint pick and place task. Findings indicate that reach-normalized distance measures, between participants and objects/targets, could accurately predict pick-up and pass decisions. Findings also reveal that participants took longer to pick-up objects where division of labor boundaries were less obvious and tended to pass in locations maximizing the dyad's efficiency. This study supports the notion that individuals are more likely to engage in interpersonal behavior when a task goal is perceived as difficult or unattainable (i.e., not afforded). Implications of findings for human-artificial agent interactions are discussed. 

Place, publisher, year, edition, pages
Cognitive Science Society, Inc., 2022
Series
Proceedings of the Annual Conference of the Cognitive Science Society, E-ISSN 1069-7977
Keywords
Behavioral research, Virtual reality, 'current, Affordances, Creative Commons, Decisions makings, Distance measure, Joint actions, Low-dimensional models, Motor behaviours, Pick and place, Pick and place task, Decision making, joint action, pick and place tasks
National Category
Production Engineering, Human Work Science and Ergonomics Human Computer Interaction
Research subject
Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-22228 (URN)2-s2.0-85146432948 (Scopus ID)
Conference
44th Annual Meeting of the Cognitive Science Society: Cognitive Diversity, CogSci 2022, Toronto 27 July 2022 through 30 July 2022, Code 185866
Funder
Australian Research Council, FT180100447
Note

CC BY 4.0

Creative Commons Attribution 4.0 International License (CC BY)

© 2022 The Author(s)

MJR was supported by the Australian Research Council Future Fellowship (FT180100447). The authors would like to thank Dr. Patrick Nalepka for his helpful comments and suggestions throughout this work.

Available from: 2023-02-02 Created: 2023-02-02 Last updated: 2023-05-04Bibliographically approved
Projects
Synergy Virtual Ergonomics (SVE) [20180167]; University of Skövde; Publications
Iriondo Pascual, A. (2023). Simulation-based multi-objective optimization of productivity and worker well-being. (Doctoral dissertation). Skövde: University of SkövdeHanson, L., Högberg, D., Brolin, E., Billing, E., Iriondo Pascual, A. & Lamb, M. (2022). Current Trends in Research and Application of Digital Human Modeling. In: Nancy L. Black; W. Patrick Neumann; Ian Noy (Ed.), Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021): Volume V: Methods & Approaches. Paper presented at 21st Congress of the International Ergonomics Association (IEA 2021), 13-18 June (pp. 358-366). Cham: SpringerGarcia Rivera, F., Högberg, D., Lamb, M. & Perez Luque, E. (2022). DHM supported assessment of the effects of using an exoskeleton during work. International Journal of Human Factors Modelling and Simulation, 7(3/4), 231-246Marshall, R., Brolin, E., Summerskill, S. & Högberg, D. (2022). Digital Human Modelling: Inclusive Design and the Ageing Population (1ed.). In: Sofia Scataglini; Silvia Imbesi; Gonçalo Marques (Ed.), Internet of Things for Human-Centered Design: Application to Elderly Healthcare (pp. 73-96). Singapore: Springer NatureIriondo Pascual, A., Lind, A., Högberg, D., Syberfeldt, A. & Hanson, L. (2022). Enabling Concurrent Multi-Objective Optimization of Worker Well-Being and Productivity in DHM Tools. In: Amos H. C. Ng; Anna Syberfeldt; Dan Högberg; Magnus Holm (Ed.), SPS2022: Proceedings of the 10th Swedish Production Symposium. Paper presented at 10th Swedish Production Symposium (SPS2022), Skövde, April 26–29 2022 (pp. 404-414). Amsterdam; Berlin; Washington, DC: IOS PressIriondo Pascual, A., Smedberg, H., Högberg, D., Syberfeldt, A. & Lämkull, D. (2022). Enabling Knowledge Discovery in Multi-Objective Optimizations of Worker Well-Being and Productivity. Sustainability, 14(9), Article ID 4894. Lamb, M., Brundin, M., Perez Luque, E. & Billing, E. (2022). Eye-Tracking Beyond Peripersonal Space in Virtual Reality: Validation and Best Practices. Frontiers in Virtual Reality, 3, Article ID 864653. Hanson, L., Högberg, D., Iriondo Pascual, A., Brolin, A., Brolin, E. & Lebram, M. (2022). Integrating Physical Load Exposure Calculations and Recommendations in Digitalized Ergonomics Assessment Processes. In: Amos H. C. Ng; Anna Syberfeldt; Dan Högberg; Magnus Holm (Ed.), SPS2022: Proceedings of the 10th Swedish Production Symposium. Paper presented at 10th Swedish Production Symposium (SPS2022), Skövde, April 26–29 2022 (pp. 233-239). Amsterdam; Berlin; Washington, DC: IOS PressIriondo Pascual, A., Högberg, D., Syberfeldt, A., Brolin, E., Perez Luque, E., Hanson, L. & Lämkull, D. (2022). Multi-objective Optimization of Ergonomics and Productivity by Using an Optimization Framework. In: Nancy L. Black; W. Patrick Neumann; Ian Noy (Ed.), Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021): Volume V: Methods & Approaches. Paper presented at 21st Congress of the International Ergonomics Association (IEA 2021), 13-18 June, 2021 (pp. 374-378). Cham: SpringerGarcía Rivera, F., Lamb, M., Högberg, D. & Brolin, A. (2022). The Schematization of XR Technologies in the Context of Collaborative Design. In: Amos H. C. Ng; Anna Syberfeldt; Dan Högberg; Magnus Holm (Ed.), SPS2022: Proceedings of the 10th Swedish Production Symposium. Paper presented at 10th Swedish Production Symposium (SPS2022), Skövde, April 26–29 2022 (pp. 520-529). Amsterdam; Berlin; Washington, DC: IOS Press
ADOPTIVE – Automated Design & Optimisation of Vehicle Ergonomics [20200003]; University of Skövde; Publications
Perez Luque, E., Brolin, E., Högberg, D. & Lamb, M. (2022). Challenges for the Consideration of Ergonomics in Product Development in the Swedish Automotive Industry – An Interview Study. In: DESIGN2022: . Paper presented at DESIGN2022, 17th International Design Conference, May, 23-26, 2022, Croatia (pp. 2165-2174). Cambridge University Press, 2Hanson, L., Högberg, D., Brolin, E., Billing, E., Iriondo Pascual, A. & Lamb, M. (2022). Current Trends in Research and Application of Digital Human Modeling. In: Nancy L. Black; W. Patrick Neumann; Ian Noy (Ed.), Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021): Volume V: Methods & Approaches. Paper presented at 21st Congress of the International Ergonomics Association (IEA 2021), 13-18 June (pp. 358-366). Cham: SpringerMarshall, R., Brolin, E., Summerskill, S. & Högberg, D. (2022). Digital Human Modelling: Inclusive Design and the Ageing Population (1ed.). In: Sofia Scataglini; Silvia Imbesi; Gonçalo Marques (Ed.), Internet of Things for Human-Centered Design: Application to Elderly Healthcare (pp. 73-96). Singapore: Springer NatureKolbeinsson, A., Brolin, E. & Lindblom, J. (2021). Data-Driven Personas: Expanding DHM for a Holistic Approach. In: Julia L. Wright; Daniel Barber; Sofia Scataglini; Sudhakar L. Rajulu (Ed.), Advances in Simulation and Digital Human Modeling: Proceedings of the AHFE 2021 Virtual Conferences on Human Factors and Simulation, and Digital Human Modeling and Applied Optimization, July 25-29, 2021, USA. Paper presented at International Conference on Applied Human Factors and Ergonomics (AHFE 2021), USA, July 25-29, 2021. (pp. 296-303). Springer, 264Brolin, E., Högberg, D. & Hanson, L. (2020). Skewed Boundary Confidence Ellipses for Anthropometric Data. In: Lars Hanson, Dan Högberg, Erik Brolin (Ed.), DHM2020: Proceedings of the 6th International Digital Human Modeling Symposium, August 31 – September 2, 2020. Paper presented at 6th International Digital Human Modeling Symposium, August 31 – September 2, 2020, Skövde, Sweden (pp. 18-27). Amsterdam: IOS PressBrolin, E., Högberg, D. & Nurbo, P. (2020). Statistical Posture Prediction of Vehicle Occupants in Digital Human Modelling Tools. In: Vincent G. Duffy (Ed.), Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. Posture, Motion and Health: 11th International Conference, DHM 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Copenhagen, Denmark, July 19–24, 2020, Proceedings, Part I. Paper presented at 11th International Conference, DHM 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Copenhagen, Denmark, July 19–24, 2020 (pp. 3-17). Cham: Springer
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