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Peripersonal Space Tele-Operation in Virtual Reality: The Role of Tactile - Force Feedback

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Haptic Interaction (AsiaHaptics 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14063))

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Abstract

In tele-operated human-robot collaboration, a human operator typically engages with a distant physical environment through a robotic system equipped with multiple sensors and actuators, allowing for haptic-based precise manipulation. Although these technical systems have been in use for years, the connection between multisensory perception and action in peripersonal space during tele-operations remains less understood. To delve deeper into this relationship, we examined distance perception in virtual peripersonal space. Participants wore an HTC Vive head-mounted display (HMD) featuring integrated eye-tracking (SMI) and moved a comparison object (a yellow ball) towards a target object (a blue ball) using a Geomagic Touch haptic device stylus, receiving either force feedback (‘closed-loop’) or no force feedback (‘open loop’) during the operation. They were instructed to focus on fixation points while performing the task, with SMI eye-tracking monitoring their gaze. The spatial positions of the comparison and target objects were arranged in four layouts: (i) center-to-center, (ii) center-to-peripheral (20 degrees in visual eccentricity), (iii) peripheral-to-center, and (iv) peripheral-to-peripheral. We employed seven distance levels between the objects in Experiment 1 and five distance levels in Experiment 2, using consistent methods of stimuli presentation. The findings revealed that estimation errors were significantly influenced by force feedback, spatial arrangement, and distance. Crucially, the visibility of the movement trajectory enhanced the effectiveness of tactile force feedback. Overall, this study proposes a potential guideline for human-computer ergonomic design, emphasizing the importance of force feedback for accurate targeting.

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References

  1. Ernst, M.O., Banks, M.S.: Humans integrate visual and haptic information in a statistically optimal fashion. Nature 415(6870), 429–433 (2002)

    Article  Google Scholar 

  2. Hillis, J.M., Ernst, M.O., Banks, M.S., Landy, M.S.: Combining sensory information: mandatory fusion within, but not between, senses. Science 298(5598), 1627–1630 (2002)

    Article  Google Scholar 

  3. Kording, K.P., Wolpert, D.M.: Bayesian integration in sensorimotor learning. Nature 427(6971), 244–247 (2004)

    Article  Google Scholar 

  4. Popescu, V.G., Burdea, G.C., Bouzit, M., Hentz, V.R.: A virtual-reality-based telerehabilitation system with force feedback. IEEE Trans. Inf Technol. Biomed. 4(1), 45–51 (2000)

    Article  Google Scholar 

  5. Pacchierotti, C., Tirmizi, A., Bianchini, G., Prattichizzo, D.: Enhancing the performance of passive teleoperation systems via cutaneous feedback. IEEE Trans. Haptics 8(4), 397–409 (2015)

    Article  Google Scholar 

  6. Neupert, C., Matich, S., Scherping, N., Kupnik, M., Werthschützky, R., Hatzfeld, C.: Pseudo-haptic feedback in teleoperation. IEEE Trans. Haptics 9(3), 397–408 (2016)

    Google Scholar 

  7. Panzirsch, M., Balachandran, R., Weber, B., Ferre, M., Artigas, J.: Haptic augmentation for teleoperation through virtual grasping points. IEEE Trans. Haptics 11(3), 400–416 (2018)

    Article  Google Scholar 

  8. Bugdadi, A., et al.: Is virtual reality surgical performance influenced by force feedback device utilized? J. Surg. Educ. 76(1), 262–273 (2019)

    Article  Google Scholar 

  9. Wang, Z., Sun, Y., Liang, B.: Synchronization control for bilateral teleoperation system with position error constraints: a fixed-time approach. ISA Trans. 93, 125–136 (2019)

    Article  Google Scholar 

  10. Swan, J., Singh, G., Ellis, S.: Matching and reaching depth judgments with real and augmented reality targets. IEEE Trans. Visual Comput. Graphics 21(11), 1289–1298 (2015)

    Article  Google Scholar 

  11. Wall, S.A., Harwerth, R.S.: Quantification of the effects of haptic feedback during a motor skills task in a simulated environment. In: Proceedings at Phantom User Research Symposium, Zurich, Switserland, pp. 61–69 (2000)

    Google Scholar 

  12. Bergamasco, M., Avizzano, C.A., Frisoli, A., Ruffaldi, E., Marcheschi, S.: (2006) Design and validation of a complete haptic system for manipulative tasks. Adv. Robot. 20(3), 367–389 (2006)

    Article  Google Scholar 

  13. Wall, S.A., Paynter, K., Shillito, A.M., Wright, M., Scali, S.: The effect of haptic feedback and stereo graphics in a 3D target acquisition task. In: Proceedings of Eurohaptics, Edinburgh, UK, pp. 23–29 (2002)

    Google Scholar 

  14. Pawar, V.M., Steed, A.: Evaluating the influence of haptic force-feedback on 3D selection tasks using natural egocentric gestures. In: IEEE Virtual Reality, Lafayette, Louisiana, USA, pp. 11–18 (2009)

    Google Scholar 

  15. Pawar, V.M., Steed, A.: Profiling the behaviour of 3D selection tasks on movement time when using natural haptic pointing gestures. In: Proceedings of the 16th ACM Symposium on Virtual Reality Software and Technology, New York, United States, pp. 79–82 (2009)

    Google Scholar 

  16. Pawar, V.M., Steed, A.: Poster: the effect of target size and force feedback on 3D selection within a co-located visual-haptic immersive virtual environment. In: 2013 IEEE Symposium on 3D User Interfaces (3DUI) 2013, Orlando, FL, USA, pp. 169–170 (2013)

    Google Scholar 

  17. Xing, J., Heeger, D.J.: Center-surround interactions in foveal and peripheral vision. Vision. Res. 40(22), 3065–3072 (2000)

    Article  Google Scholar 

  18. Latham, K., Whitaker, D.: Relative roles of resolution and spatial interference in foveal and peripheral vision. Ophthalmic Physiol. Opt. 16(1), 49–57 (1996)

    Article  Google Scholar 

  19. Siderov, J., Harwerth, R.S.: Stereopsis, spatial frequency and retinal eccentricity. Vision. Res. 35(16), 2329–2337 (1995)

    Article  Google Scholar 

  20. Thibos, L.N., Walsh, D.J., Cheney, F.E.: Vision beyond the resolution limit: aliasing in the periphery. Vision. Res. 27(12), 2193–2197 (1987)

    Article  Google Scholar 

  21. Katzakis, N., Chen, L., Ariza, O., Teather, R.J., Steinicke, F.: Evaluation of 3D pointing accuracy in the fovea and periphery in immersive head-mounted display environments. IEEE Trans. Visual Comput. Graphics 27(3), 1929–1936 (2021)

    Article  Google Scholar 

  22. de Haan, A.M., Smit, M., Van der Stigchel, S., Dijkerman, H.C.: Approaching threat modulates visuotactile interactions in peripersonal space. Exp. Brain Res. 234, 1875–1884 (2016)

    Article  Google Scholar 

  23. Chen, Y.C., Maurer, D., Lewis, T.L., Spence, C., Shore, D.I.: Central–peripheral differences in audiovisual and visuotactile event perception. Atten. Percept. Psychophys. 79, 2552–2563 (2017)

    Article  Google Scholar 

  24. Grechuta, K., Guga, J., Maffei, G., Rubio Ballester, B., Verschure, P.F.M.J.: Visuotactile integration modulates motor performance in a perceptual decision-making task. Sci. Reports 7(1), 3333 (2017)

    Google Scholar 

  25. Foley, A.J., Michaluk, L.M., Thomas, D.G.: Pace alteration and estimation of time intervals. Percept. Mot. Skills 98(1), 291–298 (2004)

    Article  Google Scholar 

  26. Rammsayer, T., Wittkowski, K.M.: Time order error and position effect of a standardized stimulus in discrimination of short time duration. Arch. Psychol. (Frankf) 142(2), 81–89 (1990)

    Google Scholar 

  27. Roy, M.M., Christenfeld, N.J.: Effect of task length on remembered and predicted duration. Psychon. Bull. Rev. 15(1), 202–207 (2008)

    Article  Google Scholar 

  28. Ryan, L.J., Havens, A.: Responses contribute to context effects on ratio-setting timing tasks. Perception 42(5), 537–550 (2013)

    Article  Google Scholar 

  29. Schiffman, H.R., Bobko, D.J.: The role of number and familiarity of stimuli in the perception of brief temporal intervals. Am. J. Psychol. 90(1), 85–93 (1977)

    Article  Google Scholar 

  30. Vatakis, A., Ulrich, R.: Temporal processing within and across senses. Acta Physiol. (Oxf) 147, 1 (2014)

    Google Scholar 

  31. Serino, A., Haggard, P.: Touch and the body. Neurosci. Biobehav. Rev. 34(2), 224–236 (2010)

    Article  Google Scholar 

  32. Hara, M., et al.: Voluntary self-touch increases body ownership. Front. Psychol. 6, 1509 (2015)

    Article  Google Scholar 

  33. Michalka, S.W., Kong, L., Rosen, M.L., Shinn-Cunningham, B.G., Somers, D.C.: Short-term memory for space and time flexibly recruit complementary sensory-biased frontal lobe attention networks. Neuron 87(4), 882–892 (2015)

    Article  Google Scholar 

  34. Rim, S., Uleman, J.S., Trope, Y.: Spontaneous trait inference and construal level theory: psychological distance increases nonconscious trait thinking. J. Exp. Soc. Psychol. 45(5), 1088–1097 (2009)

    Article  Google Scholar 

  35. Trope, Y., Liberman, N.: Construal-level theory of psychological distance. Psychol. Rev. 117(2), 440–463 (2010)

    Article  Google Scholar 

  36. Trautmann, S.T., van de Kuilen, G.: Prospect theory or construal level theory? Diminishing sensitivity vs. psychological distance in risky decisions. Acta Psychol. 139(1), 254–260 (2012)

    Google Scholar 

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Acknowledgements

This study was funded by STI2030-Major Projects 2021ZD0202600 and Sino-German Crossmodal Learning Project from Natural Science Foundation of China (Grant No. 62061136001).

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Authors and Affiliations

  1. School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, 100871, China

    Yiru Liu & Lihan Chen

  2. Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, 100871, China

    Yiru Liu & Lihan Chen

  3. Department of Informatics, Universität Hamburg, Hamburg, Germany

    Nicholas Katzakis & Frank Steinicke

  4. National Engineering Laboratory for Big Data Analysis and Applications, Peking University, Beijing, 100871, China

    Lihan Chen

Authors
  1. Yiru Liu
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  2. Nicholas Katzakis
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  3. Frank Steinicke
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  4. Lihan Chen
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Corresponding author

Correspondence to Lihan Chen .

Editor information

Editors and Affiliations

  1. Beihang University, Beijing, China

    Dangxiao Wang

  2. Southeast University, Nanjing, China

    Aiguo Song

  3. Dalian University of Technology, Dalian, China

    Qian Liu

  4. Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea (Republic of)

    Ki-Uk Kyung

  5. Tohoku University, Sendai, Japan

    Masashi Konyo

  6. The University of Electro-Communications, Tokyo, Tokyo, Japan

    Hiroyuki Kajimoto

  7. Peking University, Beijing, China

    Lihan Chen

  8. Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea (Republic of)

    Jee-Hwan Ryu

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Liu, Y., Katzakis, N., Steinicke, F., Chen, L. (2023). Peripersonal Space Tele-Operation in Virtual Reality: The Role of Tactile - Force Feedback. In: Wang, D., et al. Haptic Interaction. AsiaHaptics 2022. Lecture Notes in Computer Science, vol 14063. Springer, Cham. https://doi.org/10.1007/978-3-031-46839-1_13

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  • DOI: https://doi.org/10.1007/978-3-031-46839-1_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-46838-4

  • Online ISBN: 978-3-031-46839-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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