Advertisement

Evaluation of Haptic Feedback in the Performance of a Teleoperated Unmanned Ground Vehicle in an Obstacle Avoidance Scenario

  • Chanyoung Ju
  • Hyoung Il Son
Regular Papers Robot and Applications
  • 20 Downloads

Abstract

This study investigates the effect of haptic feedback on the teleoperation system. The performance of a teleoperated unmanned ground vehicle (UGV) was analyzed in terms of the stability, task performance, and control effort of the operator. The UGV navigation task was performed as a benchmark test for evaluation. The haptic feedback applies a potential function based on an obstacle avoidance algorithm in which the operator receives a repulsive force feedback. Psychophysical experiments were performed with three experimental cases to measure nine performance metrics. A one-way analysis of variance and post-hoc analysis were performed for the statistical analysis. In conclusion, the effect of haptic feedback is superior in terms of stability and task performance, but not in terms of control effort.

Keywords

Haptic feedback obstacle avoidance psychophysical evaluation teleoperation unmanned ground vehicle 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    P. F. Hokayem and M. W. Spong, “Bilateral teleoperation: an historical survey,” Automatica, vol. 42, no. 12, pp. 2035–2057, 2006.MathSciNetCrossRefzbMATHGoogle Scholar
  2. [2]
    H. Lee, C. Ju, S. Park, S. Park, and H. I. Son, “Preliminary user evaluation of inaccuracy in haptic guidance for teleoperated maintenance task of nuclear power plant,” Proc. of the 14th International Conf. on Ubiquitous Robots and Ambient Intelligence, pp. 467–469, 2017.Google Scholar
  3. [3]
    C. Ju, S. Park, and H. I. Son, “Effects of the position and orientation inaccuracies in haptic guidance on the task performance in teleoperation systems,” Journal of Institute of Control, Robotics and Systems, vol. 23, no. 11, pp. 981–989, 2017.Google Scholar
  4. [4]
    C. Ju and H. I. Son, “Multiple UAV systems for agricultural applications: control, implementation, and evaluation,” Electronics, vol. 7, no. 9, pp. 162, 2018.CrossRefGoogle Scholar
  5. [5]
    J. Katrasnik, F. Pernus, and B. Likar, “A survey of mobile robots for distribution power line inspection,” IEEE Transactions on Power Delivery, vol. 25, no. 1, pp. 485–493, 2010.CrossRefGoogle Scholar
  6. [6]
    M. Jung and J. B. Song, “Efficient autonomous global localization for service robots using dual laser scanners and rotational motion,” International Journal of Control, Automation and Systems, vol. 15, no. 2, pp. 743–751, 2017.CrossRefGoogle Scholar
  7. [7]
    H. G. Lee, H. J. Hyung, and D. W. Lee, “Egocentric teleoperation approach,” International Journal of Control, Automation and Systems, vol. 15, no. 6, pp. 2744–2753, 2017.CrossRefGoogle Scholar
  8. [8]
    L. Meli, C. Pacchierotti, and D. Prattichizzo, “Experimental evaluation of magnified haptic feedback for robotassisted needle insertion and palpation,” The International Journal of Medical Robotics and Computer Assisted Surgery, vol. 13, no. 4, e1809, 2017.CrossRefGoogle Scholar
  9. [9]
    C. Pacchierotti, A. Tirmizi, G. Bianchini, and D. Prattichizzo, “Enhancing the performance of passive teleoperation systems via cutaneous feedback,” IEEE Transactions on haptics, vol. 8, no. 4, pp. 397–409, 2015.CrossRefGoogle Scholar
  10. [10]
    C. E. Lathan and M. Tracey, “The effects of operator spatial perception and sensory feedback on human–robot teleoperation performance,” Presence: Teleoperators and Virtual Environments, vol. 11, no. 4, pp. 368–377, 2002.CrossRefGoogle Scholar
  11. [11]
    A. Hong, D. G. Lee, H. H. Bulthoff, and H. I. Son, “Multimodal feedback for teleoperation of multiple mobile robots in an outdoor environment,” Journal on Multimodal User Interfaces, vol. 11, no. 1, pp. 67–80, 2017.CrossRefGoogle Scholar
  12. [12]
    B. Petzold, M. F. Zaeh, B. Faerber, B. Deml, H. Egermeier, J. Schilp, and S. Clarke, “A study on visual, auditory, and haptic feedback for assembly tasks,” Presence: Teleoperators and Virtual Environments, vol. 13, no. 1, pp. 16–21, 2004.CrossRefGoogle Scholar
  13. [13]
    M. Tavakoli, A. Aziminejad, R. V. Patel, and M. Moallem, “High–fidelity bilateral teleoperation systems and the effect of multimodal haptics,” IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), vol. 37, no. 6, pp. 1512–1528, 2007.CrossRefGoogle Scholar
  14. [14]
    H. I. Son, L. L. Chuang, J. Kim, and H. H. Bulthoff, “Haptic feedback cues can improve human perceptual awareness in multi–robots teleoperation,” Proc. of the 11th International Conf. on Control, Automation and Systems, pp. 1323.1328, 2017.Google Scholar
  15. [15]
    S. Lichiardopol, “A survey on teleoperation,” Technische Universitat Eindhoven, DCT report, 2007.Google Scholar
  16. [16]
    A. Bolopion and S. Regnier, “A review of haptic feedback teleoperation systems for micromanipulation and microassembly,” IEEE Transactions on Automation Science and Engineering, vol. 10, no. 3, pp. 496–502, 2013.CrossRefGoogle Scholar
  17. [17]
    D. Lee, A. Franchi, H. I. Son, C. Ha, H. H. Bulthoff, and P. R. Giordano, “Semiautonomous haptic teleoperation control architecture of multiple unmanned aerial vehicles,” IEEE/ASME Transactions on Mechatronics, vol. 18, no. 4, pp. 1334–1345, 2013.CrossRefGoogle Scholar
  18. [18]
    S. Lee, G. S. Sukhatme, G. J. Kim, and C. M. Park, “Haptic control of a mobile robot: a user study,” Proc. of the 15th International Conf. on Intelligent Robots and Systems, Vol. 3, pp. 2867.2874, 2002.Google Scholar
  19. [19]
    S. Lee, G. J. Kim, G. S. Sukhatme, and C. M. Park, “Effects of haptic feedback on telepresence and navigational performance,” Proc. of the International Conf. on Artificial Telexistence, 2004.Google Scholar
  20. [20]
    A. Hacinecipoglu, E. I. Konukseven, and A. B. Koku, “Evaluation of haptic feedback cues on vehicle teleoperation performance in an obstacle avoidance scenario,” Proc. of the IEEE Conf. on World Haptics, pp. 689–694, 2013.Google Scholar
  21. [21]
    I. Farkhatdinov, and J. H. Ryu, “Improving mobile robot bilateral teleoperation by introducing variable force feedback gain,” Proc. of the 10th International Conf. on Intelligent Robots and Systems, pp. 5812.5817, 2010.Google Scholar
  22. [22]
    I. Farkhatdinov, J. H. Ryu, and J. Poduraev, “A user study of command strategies for mobile robot teleoperation,” Intelligent Service Robotics, vol. 2, no. 2, pp. 95–104, 2009.CrossRefGoogle Scholar
  23. [23]
    H. I. Son, A. Franchi, L. L. Chuang, J. Kim, H. H. Bulthoff, and P. R. Giordano, “Human–centered design and evaluation of haptic cueing for teleoperation of multiple mobile robots,” IEEE Transactions on Cybernetics, vol. 43, no. 2, pp. 597–609, 2013.CrossRefGoogle Scholar
  24. [24]
    A. Yamamuro, K. Tanida, and K. Ohnishi, “Evaluation of maneuverability in teleoperation based on operational effort,” Proc. of the IEEE 13th International Conf. on Industrial Informatics, pp. 343–348, 2015.Google Scholar
  25. [25]
    T. Fukao, H. Nakagawa, and N. Adachi, “Adaptive tracking control of a nonholonomic mobile robot,” IEEE Transactions on Robotics and Automation, vol. 16, no. 5, pp. 609–615, 2000.CrossRefGoogle Scholar
  26. [26]
    R. M. Murray and M. Richard, A Mathematical Introduction to Robotic Manipulation, CRC press, 2017.CrossRefzbMATHGoogle Scholar
  27. [27]
    A. Franchi, C. Secchi, H. I. Son, H. H. Bulthoff, and P. R. Giordano, “Bilateral teleoperation of groups of mobile robots with time–varying topology,” IEEE Transactions on Robotics, vol. 28, no. 5, pp. 1019–1033, 2012.CrossRefGoogle Scholar
  28. [28]
    S. G. Hart, “NASA–task load index (NASA–TLX); 20 years later,” Proceedings of the Human Factors and Ergonomics Society Annual Meeting vol. 50, no. 9, pp. 904–908, 2006.Google Scholar
  29. [29]
    S. Patrinostro, M. Tanzini, M. Satler, E. Ruffaldi, A. Filippeschi, and C. A. Avizzano, “A Haptic–assisted guidance system for working machines based on virtual force fields,” Proc. of the International Conf. on Information, Communication and Automation Technologies, pp. 1–6, 2015.Google Scholar

Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Rural and Biosystems EngineeringChonnam National UniversityGwangjuKorea

Personalised recommendations