Towards natural handshakes for social robots: human-aware hand grasps using tactile sensors

  • 1 Institute for Systems and Robotics, Instituto Superior Técnico, University of Lisbon,, Lisbon, Portugal

Abstract

Handshaking is a fundamental part of human physical interaction that is transversal to various cultural backgrounds. It is also a very challenging task in the field of Physical Human-Robot Interaction (pHRI), requiring compliant force control in order to plan the arm’s motion and for a confident, but at the same time pleasant grasp of the human user’s hand. In this paper,we focus on the study of the hand grip strength for comfortable handshakes and perform three sets of physical interaction experiments between twenty human subjects in the first experiment, thirty-five human subjects in the second one, and thirty-eight human subjects in the third one. Tests are made with a social robot whose hands are instrumented with tactile sensors that provide skin-like sensation. From these experiments, we: (i) learn the preferred grip closure according to each user group; (ii) analyze the tactile feedback provided by the sensors for each closure; (iii) develop and evaluate the hand grip controller based on previous data. In addition to the robot-human interactions, we also learn about the robot executed handshake interactions with inanimate objects, in order to detect if it is shaking hands with a human or an inanimate object. This work adds physical human-robot interaction to the repertory of social skills of our robot, fulfilling a demand previously identified by many users of the robot.

If the inline PDF is not rendering correctly, you can download the PDF file here.

  • [1] T. Paulino, P. Ribeiro, M. Neto, S. Cardoso, A. Schmitz, J. Santos- Victor, et al., Low-cost 3-axis soft tactile sensors for the humanfriendly robot vizzy, In: 2017 IEEE International Conference on Robotics and Automation (ICRA 2017), 2017, 966-971

  • [2] A. Chortos, J. Liu, Z. Bao, Pursuing prosthetic electronic skin, Nature Materials, 2016, 15(9), 937-950

  • [3] A. De Santis, B. Siciliano, A. De Luca, A. Bicchi, An atlas of physical human-robot interaction, Mechanism andMachine Theory, 2008, 43(3), 253-270

  • [4] Y. S. Sefidgar, K. E. MacLean, S. Yohanan, H. M. Van der Loos, E. A. Croft, E. J. Garland, Design and evaluation of a touchcentered calming interaction with a social robot, IEEE Transactions on Affective Computing, 2016, 7(2), 108-121

  • [5] S. Soyguder, T. Abut, Haptic industrial robot control with variable time delayed bilateral teleoperation, Industrial Robot: An International Journal, 2016, 43(4), 390-402

  • [6] T. Kasuga M. Hashimoto, Human-robot handshaking using neural oscillators, In: 2005 IEEE International Conference on Robotics and Automation (ICRA 2005), 2005, 3802-3807

  • [7] D. Papageorgiou Z. Doulgeri, A kinematic controller for humanrobot handshaking using internal motion adaptation, In: 2015 IEEE International Conference on Robotics and Automation (ICRA 2015), 2015, 5622-5627

  • [8] K. Ouchi S. Hashimoto, Handshake telephone system to communicate with voice and force, In: 6th IEEE International Workshop on Robot and HumanCommunication, RO-MAN’97 SENDAI, 1997, 466-471

  • [9] Y. Yamato, M. Jindai, T. Watanabe, Development of a shakemotion leading model for human-robot handshaking, In: 2008 SICE Annual Conference, 2008, 502-507

  • [10] M. Jindai T. Watanabe, Development of a handshake robot system based on a handshake approaching motion model, In: 2007 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, 2007, 1-6

  • [11] M. Jindai, S. Ota, Y. Ikemoto, T. Sasaki, Handshake request motion model with an approaching human for a handshake robot system, In: 2015 IEEE 7th International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM), 2015, 265-270

  • [12] M. Jindai T.Watanabe, Development of a handshake request motion model based on analysis of handshake motion between humans, In: 2011 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), 2011, 560-565

  • [13] S. Ota, M. Jindai, T. Fukuta, T. Watanabe, A handshake response motion model during active approach to a human, In: 2014 IEEE/SICE International Symposium on System Integration, 2014, 310-315

  • [14] S. Ota, M. Jindai, T. Sasaki, Y. Ikemoto, Handshake response motion model with approaching of human based on an analysis of human handshake motions, In: 2015 7th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), 2015, 8-13

  • [15] A. Melnyk, P. Henaff, V. Khomenko, V. Borysenko, Sensor network architecture tomeasure characteristics of a handshake between humans, In: 2014 IEEE 34th International Scientific Conference on Electronics and Nanotechnology (ELNANO), 2014, 264-268

  • [16] G. Avraham, I. Nisky, H. L. Fernandes, D. E. Acuna, K. P. Kording, G. E. Loeb, et al., Toward perceiving robots as humans: Three handshake models face the turing-like handshake test, IEEE Transactions on Haptics, Third 2012, 5(3), 196-207, ISSN 1939-1412

  • [17] N. Pedemonte, T. Laliberté, C. Gosselin, Design, control, and experimental validation of a handshaking reactive robotic interface, Journal of Mechanisms and Robotics, 2016, 8(1), 011020

  • [18] E. Knoop, M. Bächer, P. Beardsley, Contact pressure distribution as an evaluation metric for human-robot hand interactions, In: HRI 2017 workshop - Towards reproducible HRI Experiments: Scientific endeavors, benchmarking and standardization, 2017

  • [19] P. Orefice, M. Ammi, M. Hafez, A. Tapus, Let’s handshake and i’ll know who you are: Gender and personality discrimination in human-human and human-robot handshaking interaction, In: 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids), 2016, 958-965

  • [20] D. S. Chathuranga, Z. Wang, Y. Noh, T. Nanayakkara, S. Hirai, Robust real time material classification algorithm using soft three axis tactile sensor: Evaluation of the algorithm, In: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015, 2093-2098

  • [21] S. Luo, W. Mou, M. Li, K. Althoefer, H. Liu, Rotation and translation invariant object recognition with a tactile sensor, In: SENSORS, 2014 IEEE. IEEE, 2014, 1030-1033

  • [22] A. Khasnobish, G. Singh, A. Jati, A. Konar, D. Tibarewala, Objectshape recognition and 3d reconstruction from tactile sensor images, Medical & biological engineering & computing, 2014, 52 (4), 353-362

  • [23] P. Moreno, R. Nunes, R. Figueiredo, R. Ferreira, A. Bernardino, J. Santos-Victor, et al., Vizzy: A humanoid on wheels for assistive robotics, In: Robot 2015: Second Iberian Robotics Conference, 2016, 17-28

  • [24] H. Sakoe S. Chiba, Dynamic programming algorithm optimization for spoken word recognition, IEEE transactions on acoustics, speech, and signal processing, 1978, 26(1), 43-49

  • [25] H. Ding, G. Trajcevski, P. Scheuermann, X. Wang, E. Keogh, Querying and mining of time series data: experimental comparison of representations and distance measures, Proceedings of the VLDB Endowment, 2008, 1(2), 1542-1552

  • [26] D. J. Berndt J. Clifford, Using dynamic time warping to find patterns in time series, In: 3rd International Conference on Knowledge Discovery and Data Mining, AAAIWS’94, 1994, 359-370

  • [27] H. Sun P. Zhang, Causal relationships between perceived enjoyment and perceived ease of use: An alternative approach, Journal of the Association for Information Systems, 2006, 7(9), 24

  • [28] W. A. Bainbridge, S. Nozawa, R. Ueda, K. Okada, M. Inaba, A methodological outline and utility assessment of sensor-based biosignal measurement in human-robot interaction, International Journal of Social Robotics, Aug 2012, 4(3), 303-316

  • [29] D. Kulić E. Croft, Physiological and subjective responses to articulated robot motion, Robotica, 2007, 25(1), 13-27, https://doi.org/10.1017/S0263574706002955

  • [30] C. Bartneck, D. Kulić, E. Croft, S. Zoghbi, Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots, International Journal of Social Robotics, Jan 2009, 1(1), 71-81, https://doi.org/10.1007/s12369-008-0001-3

  • [31] J. G. Ziegler N. B. Nichols, Optimum settings for automatic controllers, Journal of Dynamic Systems, Measurement, and Control, 1942, 115(2B), 220-222

  • [32] Z. Wang, J. Yuan, M. Buss, Modelling of human haptic skill: a framework and preliminary results, Proceedings of the 17th IFAC World Congress, 2008, 41(2), 14761-14766

  • [33] W. F. Chaplin, J. B. Phillips, J. D. Brown, N. R. Clanton, J. L. Stein, Handshaking, gender, personality, and first impressions., Journal of personality and social psychology, 2000, 79(1), 110.

OPEN ACCESS

Journal + Issues

Paladyn. Journal of Behavioral Robotics is a new, peer-reviewed, electronic-only journal that publishes original, high-quality research on topics broadly related to neuronally and psychologically inspired robots and other behaving autonomous systems.

Search