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2019, 1(2): 219-232 Published Date:2019-4-20

DOI: 10.3724/SP.J.2096-5796.2019.0001

An immersive space liquid bridge experiment system with gesture interaction and vibrotactile feedback

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Abstract:

Space liquid bridge experiment is a typical space telescience experiment, which has the potential to synchronize the interaction between the human users and remote space laboratory equipment, and has high requirements on manipulation accuracy and real-time interactivity. Typical tasks in space liquid bridge experiment include bridge pulling, and clearance process etc. In order to achieve the effect of natural and immersive interaction for these tasks, a control strategy based on Leap Motion gesture interaction control and vibrotactile feedback is developed. A gesture recognition algorithm and fuzzy control algorithm based on position control are developed, and the experimental results show that the algorithms have a small memory load and a high recognition accuracy of 97.68%. We perform comparative experiments on single visual feedback and visual-tactile feedback, which verifies that the interactive effect of the visual-tactile feedback is superior to the single visual feedback. Experimental results validate that by combining Leap Motion multi-finger recognition, vibrotactile feedback and immersive display, the proposed syatem is able to achieve the goal of natural interaction for space telescience experiment.
Keywords: Space telescience experiment ; Space liquid bridge experiment ; Leap motion ; Gesture recognition algorithm

Cite this article:

Meng SONG, Shiyi LIU, Ge YU, Lili GUO, Dangxiao WANG. An immersive space liquid bridge experiment system with gesture interaction and vibrotactile feedback. Virtual Reality & Intelligent Hardware, 2019, 1(2): 219-232 DOI:10.3724/SP.J.2096-5796.2019.0001

1. Zhang Y, Li G. Concept, application and development of remote science. China Aerospace, 1997, (11), 16–20
张珩, 李庚田. 遥科学的概念、应用与发展. 中国航天. 1997, (11), 16–20

2. Fiorini P, Manzano J, Castro A. Ground-based Telerobotic Interfaces for Space Telescience. 2015

3. Chou W, Meng S, Chen J, Li S. Space science experiment robot assists remote operation system. China's space science and technology, 2003, V23(6): 7–13
丑武胜, 孟偲, 陈建新, 李晟. 空间科学实验机器人辅助遥操作系统. 中国空间科学技术, 2003, V23(6), 7–13

4. Sone Y. Robots, Space, and Place. Japanese Robot Culture. Palgrave Macmillan, US, 2017, 117–138 DOI:DOI:10.1057/978-1-137-52527-7_5

5. Liang B, Gao X , Pan L, Xu W. A formation rendezvous method of space robotic system for on-orbit service of GEO. Journal of Astronautics, 2016, 37(2): 182–188 DOI:10.3873/j.issn.1000-1328.2016.02.007

6. Creem-Regehr S H, Stefanucci J K, Thompson W B, Nash N, McCardell M. Egocentric distance perception in the Oculus Rift (DK2). In: Proceedings of the ACM SIGGRAPH Symposium on Applied Perception. Germany, ACM, 2015, 47–50 DOI:10.1145/2804408.2804422

7. Pino N. Htc vive review. 2016

8. Nutt C. PlayStation VR: Sony showed lots and lots of games today. 2015

9. Moro C, Stromberga Z, Raikos A, Stirling A. Combining virtual (Oculus Rift & Gear VR) and augmented reality with interactive applications to enhance tertiary medical and biomedical curricula. In: SIGGRAPH ASIA 2016 Symposium on Education: Talks. Macau, ACM, 2016, 1–2 DOI:10.1145/2993363.2993364

10. Mohandes M, Aliyu S, Deriche M. Arabic sign language recognition using the leap motion controller. In: 2014 IEEE 23rd International Symposium on Industrial Electronics (ISIE). 2014, 960–965 DOI:10.1109/ISIE.2014.686474

11. Lupu R G, Botezatu N, Ungureanu F, Ignat D, Moldoveanu A. Virtual reality based stroke recovery for upper limbs using leap motion. In: 2016 20th International Conference on System Theory, Control and Computing (ICSTCC). 2016, 295–299 DOI:10.1109/ICSTCC.2016.7790681

12. Connelly L, Jia Y C, Toro M L, Stoykov M E, Kenyon R V, Kamper D G. A pneumatic glove and immersive virtual reality environment for hand rehabilitative training after stroke. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2010, 18(5): 551–559 DOI:10.1109/tnsre.2010.2047588

13. Kawamura H, Ueno I, Ishikawa T. Study of thermocapillary flow in a liquid bridge towards an on-orbit experiment aboard the international space station. Advances in Space Research, 2002, 29(4): 611–618 DOI:10.1016/s0273-1177(01)00651-2

14. Velten R, Schwabe D, Scharmann A. The periodic instability of thermocapillary convection in cylindrical liquid bridges. Physics of Fluids A: Fluid Dynamics, 1991, 3(2): 267–279 DOI:10.1063/1.858135

15. Lim E, Hung Y M, Tan B T. A hydrodynamic analysis of thermocapillary convection in evaporating thin liquid films. International Journal of Heat and Mass Transfer, 2017, 108: 1103–1114 DOI:10.1016/j.ijheatmasstransfer.2016.12.111

16. Kang Q, Duan L, Zhang L, Yin Y L, Yang J S, Hu W R. Thermocapillary convection experiment facility of an open cylindrical annuli for SJ-10 satellite. Microgravity Science and Technology, 2016, 28(2): 123–132 DOI:10.1007/s12217-016-9486-9

17. Zhou J, Pan L, Ge M. Virtual visual simulation of urban lakes based on OpenSceneGraph. In: 2013 3rd International Conference on Consumer Electronics, Communications and Networks. 2013, 723–726 DOI:10.1109/CECNet.2013.6703433

18. Potter L E, Araullo J, Carter L. The Leap Motion controller: a view on sign language. In: Proceedings of the 25th Australian Computer-Human Interaction Conference: Augmentation, Application, Innovation, Collaboration. Adelaide, Australia, ACM, 2013, 175–178 DOI:10.1145/2541016.2541072

19. Bernardos A M, Sánchez J M, Portillo J I, Wang X, Besada J A, Casar J R. Design and deployment of a contactless hand-shape identification system for smart spaces. Journal of Ambient Intelligence and Humanized Computing, 2016, 7(3): 357–370 DOI:10.1007/s12652-016-0363-6

20. Vamsikrishna K M, Dogra D P, Desarkar M S. Computer-vision-assisted palm rehabilitation with supervised learning. IEEE Transactions on Biomedical Engineering, 2016, 63(5): 991–1001 DOI:10.1109/tbme.2015.2480881

21. Wang Q, Xu Y, Chen Y, Wang Y, Wu X. Dynamic hand gesture early recognition based on Hidden Semi-Markov Models. In: 2014 IEEE International Conference on Robotics and Biomimetics (ROBIO 2014). 2014, 654–658 DOI:10.1109/ROBIO.2014.7090405

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