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Breaking Down the Barriers: Investigating Non-Expert User Experiences in Robotic Teleoperation in UK and Japan

Published 24 Oct 2024 in cs.RO and cs.HC | (2410.18727v2)

Abstract: Robots are being created each year with the goal of integrating them into our daily lives. As such, there is an interest in research in evaluating the trust of humans toward robots. In addition, teleoperating robotic arms can be challenging for non-experts. To reduce the strain put on the user, we created TELESIM, a modular and plug-and-play framework that enables direct teleoperation of any robotic arm using a digital twin as the interface between users and the robotic system. We evaluated our framework using a user survey with three robots and control methods and recorded the user's workload and performance at completing a tower stacking task. However, an analysis of the strain on the user and their ability to trust robots was omitted. This paper addresses these omissions by presenting the additional results of our user survey of 37 participants carried out in United Kingdom. In addition, we present the results of an additional user survey, under similar conditions performed in Japan, with the goal of addressing the limitations of our previous approach, by interfacing a VR controller with a UR5e. Our experimental results show that the UR5e has more towers built. Additionally, the UR5e gives the least amount of cognitive stress, while the combination of Senseglove and UR3 provides the user with the highest physical strain and causes the user to feel more frustrated. Finally, the Japanese participants seem more trusting of robots than the British participants.

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References (57)
  1. Z. Shi, Y. Xie, W. Xue, Y. Chen, L. Fu, and X. Xu, “Smart factory in industry 4.0,” Systems Research and Behavioral Science, vol. 37, no. 4, pp. 607–617, 2020. [Online]. Available: https://onlinelibrary.wiley.com/doi/abs/10.1002/sres.2704
  2. B. Meindl, N. F. Ayala, J. Mendonça, and A. G. Frank, “The four smarts of industry 4.0: Evolution of ten years of research and future perspectives,” Technological Forecasting and Social Change, vol. 168, p. 120784, 2021. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S004016252100216X
  3. A. Adel, “Future of industry 5.0 in society: human-centric solutions, challenges and prospective research areas,” Journal of Cloud Computing, vol. 11, no. 1, p. 40, 2022.
  4. A. Pettinger, C. Elliott, Z. Fan, and M. Pryor, “Reducing the Teleoperator’s Cognitive Burden for Complex Contact Tasks Using Affordance Primitives,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), p. 6, 2020.
  5. F. P. Audonnet, J. Grizou, A. Hamilton, and G. Aragon-Camarasa, “TELESIM: A Modular and Plug-and-Play Framework for Robotic Arm Teleoperation using a Digital Twin,” in 2024 IEEE International Conference on Robotics and Automation (ICRA).   Yokohama, Japan: IEEE, May 2024, pp. 17 770–17 777. [Online]. Available: https://ieeexplore.ieee.org/document/10610935/
  6. C. Bartneck, T. Suzuki, T. Kanda, and T. Nomura, “The influence of people’s culture and prior experiences with Aibo on their attitude towards robots,” AI & SOCIETY, vol. 21, no. 1, pp. 217–230, Jan. 2007. [Online]. Available: https://doi.org/10.1007/s00146-006-0052-7
  7. D. Zhang, R. Tron, and R. P. Khurshid, “Haptic Feedback Improves Human-Robot Agreement and User Satisfaction in Shared-Autonomy Teleoperation,” in 2021 IEEE International Conference on Robotics and Automation (ICRA), May 2021, pp. 3306–3312, iSSN: 2577-087X.
  8. A. R. Lanfranco, A. E. Castellanos, J. P. Desai, and W. C. Meyers, “Robotic Surgery: A Current Perspective,” Annals of Surgery, vol. 239, no. 1, pp. 14–21, Jan. 2004. [Online]. Available: https://journals.lww.com/00000658-200401000-00003
  9. D. Rakita, B. Mutlu, and M. Gleicher, “A Motion Retargeting Method for Effective Mimicry-based Teleoperation of Robot Arms,” in Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction.   Vienna Austria: ACM, Mar. 2017, pp. 361–370. [Online]. Available: https://dl.acm.org/doi/10.1145/2909824.3020254
  10. K. D. Katyal, C. Y. Brown, S. A. Hechtman, M. P. Para, T. G. McGee, K. C. Wolfe, R. J. Murphy, M. D. Kutzer, E. W. Tunstel, M. P. McLoughlin, and M. S. Johannes, “Approaches to robotic teleoperation in a disaster scenario: From supervised autonomy to direct control,” in 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.   Chicago, IL, USA: IEEE, Sep. 2014, pp. 1874–1881. [Online]. Available: http://ieeexplore.ieee.org/document/6942809/
  11. R. M. Aronson, T. Santini, T. C. Kübler, E. Kasneci, S. Srinivasa, and H. Admoni, “Eye-Hand Behavior in Human-Robot Shared Manipulation,” in 2018 13th ACM/IEEE International Conference on Human-Robot Interaction (HRI), Mar. 2018, pp. 4–13, iSSN: 2167-2148.
  12. S. Scherzinger, A. Roennau, and R. Dillmann, “Learning Human-Inspired Force Strategies for Robotic Assembly,” arXiv, Tech. Rep. arXiv:2303.12440, Mar. 2023, arXiv:2303.12440 [cs] type: article. [Online]. Available: http://arxiv.org/abs/2303.12440
  13. Y. P. Toh, S. Huang, J. Lin, M. Bajzek, G. Zeglin, and N. S. Pollard, “Dexterous telemanipulation with a multi-touch interface,” in 2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012).   Osaka, Japan: IEEE, Nov. 2012, pp. 270–277. [Online]. Available: http://ieeexplore.ieee.org/document/6651531/
  14. M. Micire, M. Desai, J. L. Drury, E. McCann, A. Norton, K. M. Tsui, and H. A. Yanco, “Design and validation of two-handed multi-touch tabletop controllers for robot teleoperation,” in Proceedings of the 16th international conference on Intelligent user interfaces.   Palo Alto CA USA: ACM, Feb. 2011, pp. 145–154. [Online]. Available: https://dl.acm.org/doi/10.1145/1943403.1943427
  15. L. Wang, Q. Li, J. Lam, Z. Wang, and Z. Zhang, “Intent inference in shared-control teleoperation system in consideration of user behavior,” Complex & Intelligent Systems, Oct. 2021. [Online]. Available: https://doi.org/10.1007/s40747-021-00533-4
  16. S. Dafarra, K. Darvish, R. Grieco, G. Milani, U. Pattacini, L. Rapetti, G. Romualdi, M. Salvi, A. Scalzo, I. Sorrentino, D. Tomè, S. Traversaro, E. Valli, P. M. Viceconte, G. Metta, M. Maggiali, and D. Pucci, “iCub3 Avatar System,” arXiv, Tech. Rep. arXiv:2203.06972, Mar. 2022, arXiv:2203.06972 [cs] type: article. [Online]. Available: http://arxiv.org/abs/2203.06972
  17. A. Mandlekar, Y. Zhu, A. Garg, J. Booher, M. Spero, A. Tung, J. Gao, J. Emmons, A. Gupta, E. Orbay, S. Savarese, and L. Fei-Fei, “ROBOTURK: A Crowdsourcing Platform for Robotic Skill Learning through Imitation,” in Proceedings of The 2nd Conference on Robot Learning.   PMLR, Oct. 2018, pp. 879–893, iSSN: 2640-3498. [Online]. Available: https://proceedings.mlr.press/v87/mandlekar18a.html
  18. N. Chen, K. P. Tee, C.-M. Chew, and R. Yan, “Intuitive interaction for robotic grasping,” in Proceedings of the Workshop at SIGGRAPH Asia, ser. WASA ’12.   New York, NY, USA: Association for Computing Machinery, Nov. 2012, pp. 105–111. [Online]. Available: https://doi.org/10.1145/2425296.2425315
  19. E. Rosen, D. Whitney, E. Phillips, G. Chien, J. Tompkin, G. Konidaris, and S. Tellex, “Communicating and controlling robot arm motion intent through mixed-reality head-mounted displays,” The International Journal of Robotics Research, vol. 38, no. 12-13, pp. 1513–1526, Oct. 2019, publisher: SAGE Publications Ltd STM. [Online]. Available: https://doi.org/10.1177/0278364919842925
  20. H. Admon and S. Srinivasa, “Predicting User Intent Through Eye Gaze for Shared Autonom,” 2016 AAAI Fall Symposium Series: Shared Autonomy in Research and Practice, 2016.
  21. T.-C. Lin, A. Unni Krishnan, and Z. Li, “Shared Autonomous Interface for Reducing Physical Effort in Robot Teleoperation via Human Motion Mapping,” in 2020 IEEE International Conference on Robotics and Automation (ICRA), May 2020, pp. 9157–9163, iSSN: 2577-087X.
  22. S. Javdani, H. Admoni, S. Pellegrinelli, S. S. Srinivasa, and J. A. Bagnell, “Shared autonomy via hindsight optimization for teleoperation and teaming,” The International Journal of Robotics Research, vol. 37, no. 7, pp. 717–742, Jun. 2018, publisher: SAGE Publications Ltd STM. [Online]. Available: https://doi.org/10.1177/0278364918776060
  23. A. Gottardi, S. Tortora, E. Tosello, and E. Menegatti, “Shared Control in Robot Teleoperation With Improved Potential Fields,” IEEE Transactions on Human-Machine Systems, pp. 1–13, 2022, conference Name: IEEE Transactions on Human-Machine Systems.
  24. S. G. Hart, “Nasa-Task Load Index (NASA-TLX); 20 Years Later,” th ANNUAL MEETING, 2006.
  25. S. G. Hart and L. E. Staveland, “Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research,” in Advances in Psychology.   Elsevier, 1988, vol. 52, pp. 139–183. [Online]. Available: https://linkinghub.elsevier.com/retrieve/pii/S0166411508623869
  26. S. Parsa, H. A. Maior, A. R. E. Thumwood, M. L. Wilson, M. Hanheide, and A. G. Esfahani, “The Impact of Motion Scaling and Haptic Guidance on Operators’ Workload and Performance in Teleoperation,” in CHI Conference on Human Factors in Computing Systems Extended Abstracts.   New Orleans LA USA: ACM, Apr. 2022, pp. 1–7. [Online]. Available: https://dl.acm.org/doi/10.1145/3491101.3519814
  27. V. Moya, E. Slawiñski, V. Mut, and E. H. Couto, “Workload detection based on EEG device for teleoperation of a mobile robot,” in 2017 XVII Workshop on Information Processing and Control (RPIC), Sep. 2017, pp. 1–6. [Online]. Available: https://ieeexplore.ieee.org/document/8211636
  28. P. Naughton, J. S. Nam, A. Stratton, and K. Hauser, “Integrating Open-World Shared Control in Immersive Avatars,” in 2024 IEEE International Conference on Robotics and Automation (ICRA).   Yokohama, Japan: IEEE, May 2024, pp. 17 807–17 813. [Online]. Available: https://ieeexplore.ieee.org/document/10611618/
  29. D. Torielli, L. Franco, M. Pozzi, L. Muratore, M. Malvezzi, N. Tsagarakis, and D. Prattichizzo, “Wearable Haptics for a Marionette-inspired Teleoperation of Highly Redundant Robotic Systems,” in 2024 IEEE International Conference on Robotics and Automation (ICRA), 2024.
  30. N. Bechtel, B. Weber, P. Severin, J. Sancho Aragon, L. Van Bogaert, and M. Panzirsch, “Toward physically realistic vision in teleoperation: A user study with light-field head mounted display and 6-DoF head motion,” Journal of the Society for Information Display, vol. 31, no. 12, pp. 663–674, 2023, _eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/jsid.1262. [Online]. Available: https://onlinelibrary.wiley.com/doi/abs/10.1002/jsid.1262
  31. R. Bogue, “The first half century of industrial robot: 50 years of robotic developments,” Industrial Robot: the international journal of robotics research and application, vol. 50, no. 1, pp. 1–10, Jan. 2022, publisher: Emerald Publishing Limited. [Online]. Available: https://doi.org/10.1108/IR-10-2022-0251
  32. L. Wachowiak, O. Celiktutan, A. Coles, and G. Canal, “A Survey of Evaluation Methods and Metrics for Explanations in Human–Robot Interaction (HRI),” in 2023 IEEE International Conference on Robotics and Automation (ICRA), 2023.
  33. M. Koverola, “General Attitudes Towards Robots Scale (GAToRS): A New Instrument for Social Surveys,” International Journal of Social Robotics, 2022.
  34. C. M. Carpinella, A. B. Wyman, M. A. Perez, and S. J. Stroessner, “The Robotic Social Attributes Scale (RoSAS): Development and Validation,” in Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction.   Vienna Austria: ACM, Mar. 2017, pp. 254–262. [Online]. Available: https://dl.acm.org/doi/10.1145/2909824.3020208
  35. D. S. Syrdal, K. Dautenhahn, K. L. Koay, and M. L. Walters, “The Negative Attitudes towards Robots Scale and Reactions to Robot Behaviour in a Live Human-Robot Interaction Study,” p. 7, 2009.
  36. K. M. Tsui, M. Desai, H. A. Yanco, H. Cramer, and N. Kemper, “Using the ”negative attitude toward robots scale” with telepresence robots,” in Proceedings of the 10th Performance Metrics for Intelligent Systems Workshop on - PerMIS ’10.   Baltimore, Maryland: ACM Press, 2010, p. 243. [Online]. Available: http://dl.acm.org/citation.cfm?doid=2377576.2377621
  37. “Isaac Sim,” Dec. 2019. [Online]. Available: https:developer.nvidia.comisaac-sim
  38. S. Macenski, T. Foote, B. Gerkey, C. Lalancette, and W. Woodall, “Robot Operating System 2: Design, architecture, and uses in the wild,” Science Robotics, vol. 7, no. 66, p. eabm6074, May 2022, publisher: American Association for the Advancement of Science. [Online]. Available: https://www.science.org/doi/abs/10.1126/scirobotics.abm6074
  39. F. P. Audonnet, I. G. Ramirez-Alpizar, and G. Aragon-Camarasa, “IMMERTWIN: A Mixed Reality Framework for Enhanced Robotic Arm Teleoperation,” Sep. 2024, arXiv:2409.08964. [Online]. Available: http://arxiv.org/abs/2409.08964
  40. S. LaValle, “Rapidly-exploring random trees : a new tool for path planning,” The annual research report, 1998.
  41. D. Coleman, I. Sucan, S. Chitta, and N. Correll, “Reducing the Barrier to Entry of Complex Robotic Software: a MoveIt! Case Study,” arXiv:1404.3785 [cs], Apr. 2014, arXiv: 1404.3785. [Online]. Available: http://arxiv.org/abs/1404.3785
  42. I. A. Sucan, M. Moll, and L. E. Kavraki, “The Open Motion Planning Library,” IEEE Robotics & Automation Magazine, vol. 19, no. 4, pp. 72–82, Dec. 2012, conference Name: IEEE Robotics & Automation Magazine. [Online]. Available: https://ieeexplore.ieee.org/document/6377468/?arnumber=6377468
  43. C.-A. Cheng, M. Mukadam, J. Issac, S. Birchfield, D. Fox, B. Boots, and N. Ratliff, “RMPflow: A Computational Graph for Automatic Motion Policy Generation,” in Algorithmic Foundations of Robotics XIII, ser. Springer Proceedings in Advanced Robotics, M. Morales, L. Tapia, G. Sánchez-Ante, and S. Hutchinson, Eds.   Cham: Springer International Publishing, 2020, pp. 441–457.
  44. “Yale OpenHand Project - Model T42,” 2023. [Online]. Available: https://www.eng.yale.edu/grablab/openhand/model_t42.html
  45. “robotiq,” 2024. [Online]. Available: https://robotiq.com/products/2f85-140-adaptive-robot-gripper
  46. A. Hodrien and T. Fernando, “A review of post-study and post-task subjective questionnaires to guide assessment of system usability,” Journal of Usability Studies, vol. 16, no. 3, pp. 203–232, May 2021.
  47. S. Ruan, J. O. Wobbrock, K. Liou, A. Ng, and J. A. Landay, “Comparing Speech and Keyboard Text Entry for Short Messages in Two Languages on Touchscreen Phones,” vol. 1, no. 4, 2017.
  48. J. R. Lewis and O. Erdinç, “User experience rating scales with 7, 11, or 101 points: does it matter?” J. Usability Studies, vol. 12, no. 2, pp. 73–91, Feb. 2017.
  49. “Valve Index.” [Online]. Available: https://store.steampowered.com/valveindex
  50. S. Naneva, “A Systematic Review of Attitudes, Anxiety, Acceptance, and Trust Towards Social Robots,” International Journal of Social Robotics, 2020.
  51. S. Cremer, L. Mastromoro, and D. O. Popa, “On the performance of the Baxter research robot,” 2016.
  52. C. Nam, H. Li, S. Li, M. Lewis, and K. Sycara, “Trust of Humans in Supervisory Control of Swarm Robots with Varied Levels of Autonomy,” in 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Oct. 2018, pp. 825–830, iSSN: 2577-1655. [Online]. Available: https://ieeexplore.ieee.org/document/8616144/?arnumber=8616144
  53. A. Hamad and B. Jia, “How Virtual Reality Technology Has Changed Our Lives: An Overview of the Current and Potential Applications and Limitations,” International Journal of Environmental Research and Public Health, vol. 19, no. 18, p. 11278, Sep. 2022. [Online]. Available: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9517547/
  54. D. J. Rea and S. H. Seo, “Still Not Solved: A Call for Renewed Focus on User-Centered Teleoperation Interfaces,” Frontiers in Robotics and AI, vol. 9, 2022. [Online]. Available: https://www.frontiersin.org/articles/10.3389/frobt.2022.704225
  55. T. Muto and J.-H. Lee, “A touch based Multi-Modal interface for teleoperation to improve usability for the non-expert,” in 2012 IEEE/SICE International Symposium on System Integration (SII), Dec. 2012, pp. 589–594.
  56. F. KAPLAN, “WHO IS AFRAID OF THE HUMANOID? INVESTIGATING CULTURAL DIFFERENCES IN THE ACCEPTANCE OF ROBOTS,” International Journal of Humanoid Robotics, Jan. 2012, publisher: World Scientific Publishing Company. [Online]. Available: https://www.worldscientific.com/worldscinet/ijhr
  57. H. Osawa, D. Miyamoto, S. Hase, R. Saijo, K. Fukuchi, and Y. Miyake, “Visions of Artificial Intelligence and Robots in Science Fiction: a computational analysis,” International Journal of Social Robotics, vol. 14, no. 10, pp. 2123–2133, Dec. 2022. [Online]. Available: https://link.springer.com/10.1007/s12369-022-00876-z

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