Abstract
Collaborative robots that provide anticipatory assistance are able to help people complete tasks more quickly. As anticipatory assistance is provided before help is explicitly requested, there is a chance that this action itself will influence the person’s future decisions in the task. In this work, we investigate whether a robot’s anticipatory assistance can drive people to make choices different from those they would otherwise make. Such a study requires measuring intent, which itself could modify intent, resulting in an observer paradox. To combat this, we carefully designed an experiment to avoid this effect. We considered several mitigations such as the careful choice of which human behavioral signals we use to measure intent and designing unobtrusive ways to obtain these signals. We conducted a user study \((N=99)\) in which participants completed a collaborative object retrieval task: users selected an object and a robot arm retrieved it for them. The robot predicted the user’s object selection from eye gaze in advance of their explicit selection, and then provided either collaborative anticipation (moving toward the predicted object), adversarial anticipation (moving away from the predicted object), or no anticipation (no movement, control condition). We found trends and participant comments suggesting people’s decision making changes in the presence of a robot anticipatory motion and this change differs depending on the robot’s anticipation strategy.
B. A. Newman and A. Biswas—Contributed equally to this work.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Admoni, H., Srinivasa, S.: Predicting user intent through eye gaze for shared autonomy. In: 2016 AAAI Fall Symposium Series (2016)
Aronson, R.M., Santini, T., Kubler, T.C., Kasneci, E., Srinivasa, S., Admoni, H.: Eye-hand behavior in human-robot shared manipulation. In: ACM/IEEE International Conference on Human-Robot Interaction. ACM, New York (2018)
Chen, M., Hsu, D., Lee, W.S.: Guided exploration of human intentions for human-robot interaction. In: Morales, M., Tapia, L., Sánchez-Ante, G., Hutchinson, S. (eds.) WAFR 2018. SPAR, vol. 14, pp. 921–938. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-44051-0_53
Dragan, A.D., Bauman, S., Forlizzi, J., Srinivasa, S.S.: Effects of robot motion on human-robot collaboration. In: ACM/IEEE International Conference on Human-Robot Interaction, pp. 51–58. ACM (2015)
Durdu, A., Erkmen, I., Erkmen, A.M.: Estimating and reshaping human intention via human-robot interaction. Turk. J. Electr. Eng. Comput. Sci. 24(1), 88–104 (2016)
Fisac, J.F., Bronstein, E., Stefansson, E., Sadigh, D., Sastry, S.S., Dragan, A.D.: Hierarchical game-theoretic planning for autonomous vehicles. arXiv preprint arXiv:1810.05766 (2018)
Grigore, E.C., Eder, K., Pipe, A.G., Melhuish, C., Leonards, U.: Joint action understanding improves robot-to-human object handover. In: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4622–4629. IEEE (2013)
Hancock, P.A., Billings, D.R., Schaefer, K.E., Chen, J.Y., De Visser, E.J., Parasuraman, R.: A meta-analysis of factors affecting trust in human-robot interaction. Hum. Factors 53(5), 517–527 (2011)
Hayhoe, M., Ballard, D.: Eye movements in natural behavior. Trends Cogn. Sci. 9(4), 188–194 (2005)
Hoffman, G.: Anticipation in human-robot interaction. In: AAAI Spring Symposium Series (2010)
Huang, C.M., Andrist, S., Sauppé, A., Mutlu, B.: Using gaze patterns to predict task intent in collaboration. Front. Psychol. 6, 1049 (2015)
Huang, C.M., Mutlu, B.: Anticipatory robot control for efficient human-robot collaboration. In: ACM/IEEE International Conference on Human-Robot Interaction, pp. 83–90 (2016)
Javdani, S., Srinivasa, S.S., Bagnell, J.A.: Shared autonomy via hindsight optimization. In: Robotics Science and Systems: Online Proceedings 2015 (2015)
Johansson, R.S., Westling, G., Bäckström, A., Flanagan, J.R.: Eye-hand coordination in object manipulation. J. Neurosci. 21(17), 6917–6932 (2001)
Mathieu, J.E., Heffner, T.S., Goodwin, G.F., Salas, E., Cannon-Bowers, J.A.: The influence of shared mental models on team process and performance. J. Appl. Psychol. 85(2), 273 (2000)
Nikolaidis, S., Hsu, D., Srinivasa, S.: Human-robot mutual adaptation in collaborative tasks: models and experiments. Int. J. Robot. Res. 36, 618–634 (2017)
Pelz, J., Hayhoe, M., Loeber, R.: The coordination of eye, head, and hand movements in a natural task. Exp. Brain Res. 139(3), 266–277 (2001)
Risko, E.F., Kingstone, A.: Eyes wide shut: implied social presence, eye tracking and attention. Atten. Percept. Psychophys. 73(2), 291–296 (2011)
Sadigh, D., Landolfi, N., Sastry, S.S., Seshia, S.A., Dragan, A.D.: Planning for cars that coordinate with people: leveraging effects on human actions for planning and active information gathering over human internal state. Auton. Robots 42(7), 1405–1426 (2018). https://doi.org/10.1007/s10514-018-9746-1
Stolzenwald, J., Mayol-Cuevas, W.W.: Rebellion and obedience: the effects of intention prediction in cooperative handheld robots. In: 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019 (2019)
Wang, W., Li, R., Chen, Y., Jia, Y.: Human intention prediction in human-robot collaborative tasks. In: Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction, pp. 279–280. ACM (2018)
Yi, W., Ballard, D.H.: Recognizing behavior in hand-eye coordination patterns. Int. J. HR: Humanoid Robot. 6(3), 337–359 (2009)
Yu, C., Ballard, D.H.: Learning spoken words from multisensory input. In: 6th International Conference on Signal Processing, vol. 2, pp. 998–1001 (2002)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Newman, B.A., Biswas, A., Ahuja, S., Girdhar, S., Kitani, K.K., Admoni, H. (2020). Examining the Effects of Anticipatory Robot Assistance on Human Decision Making. In: Wagner, A.R., et al. Social Robotics. ICSR 2020. Lecture Notes in Computer Science(), vol 12483. Springer, Cham. https://doi.org/10.1007/978-3-030-62056-1_49
Download citation
DOI: https://doi.org/10.1007/978-3-030-62056-1_49
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-62055-4
Online ISBN: 978-3-030-62056-1
eBook Packages: Computer ScienceComputer Science (R0)