The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
Anticipatory robot control for efficient human-robot collaboration
Abstract
Efficient collaboration requires collaborators to monitor the behaviors of their partners, make inferences about their task intent, and plan their own actions accordingly. To work seamlessly and efficiently with their human counterparts, robots must similarly rely on predictions of their users' intent in planning their actions. In this paper, we present an anticipatory control method that enables robots to proactively perform task actions based on anticipated actions of their human partners. We implemented this method into a robot system that monitored its user's gaze, predicted his or her task intent based on observed gaze patterns, and performed anticipatory task actions according to its predictions. Results from a human-robot interaction experiment showed that anticipatory control enabled the robot to respond to user requests and complete the task faster-2.5 seconds on average and up to 3.4 seconds-compared to a robot using a reactive control method that did not anticipate user intent. Our findings highlight the promise of performing anticipatory actions for achieving efficient human-robot teamwork.
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“Prior research in the domain of human-robot collaboration has demonstrated how a robot can anticipate its human collaborator's task needs based on the observation of the collaborator's eye gaze and provide anticipatory robot assistance [29].”
From Understanding User Reliance on AI in Assisted Decision-Making (2022) · cites this paper as [29]
Citations
Cites
RRT-connect: An efficient approach to single-query path planning
Kuffner, J. J., & LaValle, S. M. (2000) · Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065) · doi:10.1109/robot.2000.844730 · Cited by 3,555
Mirror neurons and the simulation theory of mind-reading
Gallese, V (1998) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(98)01262-5 · Cited by 3,201
Joint action: bodies and minds moving together
SEBANZ, N., BEKKERING, H., & KNOBLICH, G. (2006) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2005.12.009 · Cited by 1,950
Tomasello, M. (2009) · doi:10.7551/mitpress/8470.001.0001 · Cited by 1,896
The Roles of Vision and Eye Movements in the Control of Activities of Daily Living
Land, M. F., Mennie, N. R., & Rusted, J. M. (1999) · Perception · doi:10.1068/p2935 · Cited by 1,128
Joint attention as social cognition.
Tomasello, M. (1995) · Medical Entomology and Zoology · Cited by 1,004
Eye–Hand Coordination in Object Manipulation
Johansson, R. S., Westling, G., Bäckström, A., & Flanagan, J. R. (2001) · Journal of Neuroscience · doi:10.1523/jneurosci.21-17-06917.2001 · Cited by 873
(2013) · doi:10.1109/hri.2013.6483603 · Cited by 595
Prediction in Joint Action: What, When, and Where
Sebanz, N., & Knoblich, G. (2009) · Topics in Cognitive Science · doi:10.1111/j.1756-8765.2009.01024.x · Cited by 571
Perception of Another Person's Looking Behavior
Gibson, J. J., & Pick, A. D. (1963) · The American Journal of Psychology · doi:10.2307/1419779 · Cited by 400
How we predict what other people are going to do
Frith, C., & Frith, U. (2006) · Brain Research · doi:10.1016/j.brainres.2005.12.126 · Cited by 362
Coordinating cognition: The costs and benefits of shared gaze during collaborative search
Brennan, S. E., Chen, X., Dickinson, C. A., Neider, M. B., & Zelinsky, G. J. (2007) · Cognition · doi:10.1016/j.cognition.2007.05.012 · Cited by 351
Satake, S., Kanda, T., Glas, D. F., Imai, M., Ishiguro, H., & Hagita, N. (2009) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/1514095.1514117 · Cited by 302
Human-robot collaborative manipulation planning using early prediction of human motion
Mainprice, J., & Berenson, D. (2013) · 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems · doi:10.1109/iros.2013.6696368 · Cited by 301
On the Roles of Eye Gaze and Head Dynamics in Predicting Driver's Intent to Change Lanes
Doshi, A., & Trivedi, M. M. (2009) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2009.2026675 · Cited by 299
The ontogeny and phylogeny of joint visual attention.
Butterworth, G. E. (1991) · Cited by 210
"Like Me" as a Building Block for Understanding Other Minds: Bodily Acts, Attention, and Intention
Meltzoff, A. N., & Rechele Brooks, A. (2001) · The MIT Press eBooks · doi:10.7551/mitpress/3838.003.0013 · Cited by 207
Mutlu, B., Yamaoka, F., Kanda, T., Ishiguro, H., & Hagita, N. (2009) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/1514095.1514110 · Cited by 191
Self-citationUsing gaze patterns to predict task intent in collaboration
Huang, C., Andrist, S., Sauppé, A., & Mutlu, B. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.01049 · Cited by 181
Self-citationEffects of anticipatory action on human-robot teamwork efficiency, fluency, and perception of team
Hoffman, G., & Breazeal, C. (2007) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/1228716.1228718 · Cited by 169
Boucher, J.-D., Pattacini, U., Lelong, A., Bailly, G., Elisei, F., Fagel, S., Dominey, P. F., & Ventre‐Dominey, J. (2012) · Frontiers in Neurorobotics · doi:10.3389/fnbot.2012.00003 · Cited by 151
Pérez-D’Arpino, C., & Shah, J. (2015) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2015.7140066 · Cited by 149
Joint Action: Neurocognitive Mechanisms Supporting Human Interaction
Harold Bekkering, A., de Bruijn, E. R. A., Cuijpers, R. H., Newman‐Norlund, R., van Schie, H. T., & Meulenbroek, R. G. J. (2009) · Topics in Cognitive Science · doi:10.1111/j.1756-8765.2009.01023.x · Cited by 143
Anticipating Human Activities using Object Affordances for Reactive Robotic Response
Koppula, H., & Saxena, A. (2013) · Robotics: Science and Systems IX · doi:10.15607/rss.2013.ix.006 · Cited by 130
Anticipating human actions for collaboration in the presence of task and sensor uncertainty
Hawkins, K. P., Bansal, S., Vo, N., & Bobick, A. (2014) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2014.6907165 · Cited by 79
Robot mediated round table: Analysis of the effect of robot's gaze
Imai, M., Kanda, T., Ono, T., Ishiguro, H., & Mase, K. (2003) · IEEE RO-MAN · doi:10.1109/roman.2002.1045657 · Cited by 62
Action parsing and goal inference using self as simulator
Gray, J., Breazeal, C., Berlin, M., Brooks, A., & Lieberman, J. (2006) · IEEE RO-MAN · doi:10.1109/roman.2005.1513780 · Cited by 59
RECOGNIZING BEHAVIOR IN HAND-EYE COORDINATION PATTERNS
Yi, W., & Ballard, D. H. (2009) · International Journal of Humanoid Robotics · doi:10.1142/s0219843609001863 · Cited by 49
Towards active event recognition
Ognibene, D., & Demiris, Y. (2013) · Spiral (Imperial College London) · Cited by 29
Proactive Action Preparation: Seeing Action Preparation as a Continuous and Proactive Process
Pezzulo, G., & Ognibene, D. (2012) · Motor Control · doi:10.1123/mcj.16.3.386 · Cited by 27
Experimental Design in the Behavioral and Social Sciences
Schneider, S. (2013) · SAGE Publications Ltd eBooks · doi:10.4135/9781446286326 · Cited by 8
Research works printed but not linked: 1
- seltman, 2012, Experimental Design for Behavioral and Social Sciences
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Sorted by citations
Social Eye Gaze in Human-Robot Interaction: A Review
Admoni, H., & Scassellati, B. M. (2017) · Journal of Human-Robot Interaction · doi:10.5898/jhri.6.1.admoni · Cited by 623
“Interviews can also be used to elicit anecdotal evidence that supports or explains the study’s findings (Huang & Mutlu, 2016; Mutlu, Yamaoka, Kanda, Ishiguro, & Hagita, 2009).”
BackgroundMethodArtificial Intelligence in Advanced Manufacturing: Current Status and Future Outlook
Arinez, J. F., Chang, Q., Gao, R. X., Xu, C., & Zhang, J. (2020) · Journal of Manufacturing Science and Engineering · doi:10.1115/1.4047855 · Cited by 584
“In other work [82], an “ anticipatory control ” method is developed to proactively plan robot actions based on anticipation of the human operator ’ s intention during task performance.”
Cobot programming for collaborative industrial tasks: An overview
Zaatari, S. E., Marei, M., Li, W., & Usman, Z. (2019) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2019.03.003 · Cited by 470
Hentout, A., Mustapha, A., Maoudj, A., & Akli, I. (2019) · Advanced Robotics · doi:10.1080/01691864.2019.1636714 · Cited by 463
Embodiment in Socially Interactive Robots
Deng, E., Mutlu, B., & Matarić, M. J. (2019) · Foundations and Trends in Robotics · doi:10.1561/2300000056 · Cited by 261
“approaches to human-robot collaboration, such as using cross-training to improve task sharing between human and robot workers [220], planning shared work plans taking human ergonomics into consideration [236], and adapting robot actions to human motion, availability, adaptability, and intent [127, 160, 129, 221].”
BackgroundMethodSelf-citation
Metadata
- Authors
- Huang, C.-M., & Mutlu, B.
- Affiliations
- Yale University (US)
- University of Wisconsin–Madison (US)
- Venue
- 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI)
- Publisher
- IEEE
- Published
- 2016-03
- Pages
- 83-90
- OpenAlex
- W4229726131
- Cited by
- 227
- References
- 31
- Citations by year
- 2026: 17 · 2025: 28 · 2024: 31 · 2023: 27 · 2022: 28 · 2021: 21 · 2020: 24 · 2019: 22 · 2018: 20 · 2017: 8 · 2016: 1
- FWCI
- 28.71
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- ACM/IEEE International Conference on Human-Robot Interaction (HRI) (publishedVersion)
- Funders
- National Science Foundation
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Physical Sciences › Engineering › Control and Systems Engineering › Robot Manipulation and Learning
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Keywords
- anticipatory control, human-robot collaboration, gaze prediction, human-robot interaction, task completion time
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