Abstract
Service robots are expected to closely interact with humans in the near future. Their tasks often include delivering and taking objects. Thus, handover scenarios play an important role in human-robot-interaction. A lot of work in this field of research focuses on speed, accuracy and predictability of the robot’s movement during object handover. Those robots need to closely interact with naive users and not only experts. In order to evaluate handover interaction performance between human and robot a force measurement based approach was implemented on the humanoid robot Floka. Different gestures with the second arm were added to analyze the influence on synchronization, predictability, and human acceptance. In this paper we present a study where users with different levels of experience were asked to help the robot to learn new objects. We evaluated the impact of previous knowledge with robots on handover interactions. Disparities in timing, distance, and applied force during handover could be observed. We present an automated annotation pipeline for human-robot-interaction that will be used in future studies. While the commonly used force measurement based approach proved to be a valid starting point, our results show that naive user interaction could benefit from better anticipation.
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References
Aleotti, J., Micelli, V., Caselli, S.: An affordance sensitive system for robot to human object handover. Int. J. Soc. Robot. 6(4), 653–666 (2014)
Bartneck, C., Kulić, D., Croft, E., Zoghbi, S.: Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots. Int. J. Soc. Robot. 1(1), 71–81 (2009)
Basili, P., Huber, M., Brandt, T., Hirche, S., Glasauer, S.: Investigating human-human approach and hand-over. In: Ritter, H., Sagerer, G., Dillmann, R., Buss, M. (eds.) Human Centered Robot Systems, vol. 6, pp. 151–160. Springer, Heidelberg (2009). doi:10.1007/978-3-642-10403-9_16
Bdiwi, M., Suchy, J., Winkler, A.: Handing-over model-free objects to human hand with the help of vision/force robot control. In: 10th International Multi-Conferences on Systems, Signals and Devices (SSD 2013), pp. 1–6. IEEE (2013)
Meyer zu Borgsen, S., Korthals, T., Lier, F., Wachsmuth, S.: ToBI team of Bielefeld: enhancing robot behaviors and the role of multi-robotics in RoboCup@Home. In: Behnke, S., Raymond, S., Sariel, S., Lee, D.D. (eds.) RoboCup 2016: Robot World Cup XX. LNCS (LNAI), vol. 9776. Springer, Heidelberg (2016). doi:10.1007/978-3-319-68792-6
Cakmak, M., Srinivasa, S.S., Lee, M.K., Forlizzi, J., Kiesler, S.: Human preferences for robot-human hand-over configurations. In: IEEE International Conference on Intelligent Robots and Systems, pp. 1986–1993 (2011)
Chan, W.P., Pan, M.K.X.J., Croft, E.A., Inaba, M.: Characterization of handover orientations used by humans for efficient robot to human handovers. In: IEEE International Conference on Intelligent Robots and Systems, vol. 2015, pp. 1–6, December 2015
Chan, W.P., Parker, C.A.C., Van der Loos, H.F.M., Croft, E.A.: A human-inspired object handover controller. Int. J. Robot. Res. 32(8), 971–983 (2013)
Dragan, A.D., Bauman, S., Forlizzi, J., Srinivasa, S.S.: Effects of robot motion on human-robot collaboration. In: Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction - HRI 2015, vol. 1, pp. 51–58 (2015)
Edsinger, A., Kemp, C.C.: Human-robot interaction for cooperative manipulation: handing objects to one another. In: Proceedings of IEEE International Workshop on Robot and Human Interactive Communication, pp. 1167–1172 (2007)
Grigore, E.C., Eder, K., Pipe, A.G., Melhuish, C., Leonards, U.: Joint action understanding improves robot-to-human object handover. In: IEEE International Conference on Intelligent Robots and Systems, pp. 4622–4629 (2013)
He, W., Sidobre, D.: Improving human-robot object exchange by online force classification. J. Hum. Robot Interact. 4(1), 75 (2015)
Huang, C.M., Cakmak, M., Mutlu, B.: Adaptive coordination strategies for human-robot handovers. In: Robotics: Science and Systems (2015)
Huber, M., Rickert, M., Knoll, A., Brandt, T., Glasauer, S.: Human-robot interaction in handing-over tasks. In: Proceedings of the 17th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN (2008)
Koay, K., Sisbot, E., Syrdal, D., Walters, M.: Exploratory study of a robot approaching a person in the context of handing over an object. In: AAAI Spring Symposium (2007)
Koene, A., Remazeilles, A., Prada, M., Garzo, A., Puerto, M., Endo, S., Wing, A.M.: Relative importance of spatial and temporal precision for user satisfaction in human-robot object handover interactions. In: Third International Symposium on New Frontiers in Human-Robot Interaction, p. 14 (2014)
Moon, A., Troniak, D.M., Gleeson, B., Pan, M.K., Zeng, M., Blumer, B.A., MacLean, K., Croft, E.A.: Meet me where i’m gazing. In: Proceedings of the 2014 ACM/IEEE International Conference on Human-Robot Interaction - HRI 2014, pp. 334–341. ACM, New York (2014)
Nagata, K., Oosaki, Y., Kakikura, M., Tsukune, H.: Delivery by hand between human and robot based on fingertip force-torque information. In: Proceedings of 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Innovations in Theory, Practice and Applications (Cat. No. 98CH36190), vol. 2, pp. 750–757. IEEE (1998)
Nomura, T., Suzuki, T., Kanda, T., Kato, K.: Measurement of negative attitudes toward robots. Interact. Stud. 7(3), 437–454 (2006)
Parastegari, S., Noohi, E., Abbasi, B., Žefran, M.: A fail-safe object handover controller. In: Proceedings of IEEE International Conference on Robotics and Automation, pp. 2003–2008 (2016)
Prada, M., Remazeilles, A., Koene, A., Endo, S.: Dynamic Movement Primitives for Human-Robot interaction: comparison with human behavioral observation. In: IEEE International Conference on Intelligent Robots and Systems (2013)
Prada, M., Remazeilles, A., Koene, A., Endo, S.: Implementation and experimental validation of Dynamic Movement Primitives for object handover. In: IEEE International Conference on Intelligent Robots and Systems, pp. 2146–2153 (2014)
Simon, T., Joo, H., Matthews, I., Sheikh, Y.: Hand keypoint detection in single images using multiview bootstrapping. In: Conference on Computer Vision and Pattern Recognition (2017)
Sisbot, E.A., Alami, R.: A human-aware manipulation planner. IEEE Trans. Robot. 28(5), 1045–1057 (2012)
Strabala, K., Lee, M.K., Dragan, A., Forlizzi, J., Srinavasa, S.S., Cakmak, M., Micelli, V.: Towards seamless human-robot handovers. J. Hum. Robot Interact. 1(1), 112–132 (2013)
Wei, S.E., Ramakrishna, V., Kanade, T., Sheikh, Y.: Convolutional pose machines. In: Conference on Computer Vision and Pattern Recognition (2016)
Yamane, K., Revfi, M., Asfour, T.: Synthesizing object receiving motions of humanoid robots with human motion database. In: 2013 IEEE International Conference on Robotics and Automation, pp. 1629–1636. IEEE (2013)
Acknowledgments
This research/work was supported by the Cluster of Excellence Cognitive Interaction Technology ‘CITEC’ (EXC 277) at Bielefeld University, which is funded by the German Research Foundation (DFG).
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Meyer zu Borgsen, S., Bernotat, J., Wachsmuth, S. (2017). Hand in Hand with Robots: Differences Between Experienced and Naive Users in Human-Robot Handover Scenarios. In: Kheddar, A., et al. Social Robotics. ICSR 2017. Lecture Notes in Computer Science(), vol 10652. Springer, Cham. https://doi.org/10.1007/978-3-319-70022-9_58
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DOI: https://doi.org/10.1007/978-3-319-70022-9_58
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