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Experimental Analysis of Human Control Strategies in Contact Manipulation Tasks

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2016 International Symposium on Experimental Robotics (ISER 2016)

Part of the book series: Springer Proceedings in Advanced Robotics ((SPAR,volume 1))

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Abstract

Here, we present insights into human contact-control strategies by defining conditions to determine whether a human controls a contact state, empirically analyzing object-to-environment contact geometry data obtained from human demonstrations in a haptic simulation environment, and testing hypothesess about underlying human contact-control strategies. Using haptic demonstration data from eleven subjects who inserted non-convex objects into occluded holes, we tested the following human contact-control hypotheses: (h1) humans follow a task trajectory that tracks pre-planned contact-state waypoints organized in a contact-state graph (contact-waypoint hypothesis); (h2) humans traverse the contact-state graph, explicitly controlling some contact states or subsets of contact states, in addition to the pre-determined initial and final goal states (controlled subgraph hypothesis); (h3) humans use a control policy where the only controlled states are the starting state for the task and the goal state (state policy hypothesis). Notably, we found that humans tend to visit a select few contact states once they enter each state’s vicinity in the graph, which is evidence against h3. Yet humans do not always visit said states (visit probability \(<40\%\)), which is, in addition, evidence against h1 provided different humans adopt similar strategies. We show that a classifier to determine when humans control their trajectories to visit specific contact states, when parameterized correctly, is invariant to graph aggregation operations across the false-positive to false-negative tradeoff spectrum. This indicates our results are robust given the data we obtained and suggests that efforts to characterize human motion should focus on h2.

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Notes

  1. 1.

    In this paper, we ignore contact states consisting of \((\{\mathbb {V}\}_{object} \times \{\mathbb {V}\}_{environment})\) and \((\{\mathbb {E}\}_{object} \times \{\mathbb {E}\}_{environment})\) where the edges are parallel, since they are degenerate cases.

  2. 2.

    In [10], the contact graph transition function was specifically defined to return a 1 if a given state can be reached by another without losing contact.

  3. 3.

    Human Subjects: Healthy, right-handed subjects with no history of motor disorders: 20m:6’0", 28m:5’9", 31f:5’4", 20m:6’0", 19m:6’0", 20m:5’7", 29m:5’11", 21f:5’2", 32m:5’11", 30m:5’8", 29m:5’8". Informed consent obtained in advance on a protocol approved by Stanford University’s Institutional Review Board (IRB).

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Acknowledgements

We thank Keegan Go for his assistance with developing the haptic simulation environment. The project was supported by National Science Foundation National Robotics Initiative grant (IIS-1427396, O. Khatib and R. Bajcsy) and a grant from the SAIL-Toyota Center for AI Research at Stanford (O. Khatib).

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Authors and Affiliations

  1. Stanford Robotics Lab, Department of Computer Science, Stanford University, Stanford, California, 94305, USA

    Ellen Klingbeil, Samir Menon & Oussama Khatib

Authors
  1. Ellen Klingbeil
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  2. Samir Menon
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  3. Oussama Khatib
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Corresponding author

Correspondence to Ellen Klingbeil .

Editor information

Editors and Affiliations

  1. Gra Sch of Info Sci&Tech,Dept of MechInf, The University of Tokyo Gra Sch of Info Sci&Tech,Dept of MechInf, Tokyo, Japan

    Dana Kulić

  2. Computer Science Department, Stanford University Computer Science Department, Stanford, California, USA

    Yoshihiko Nakamura

  3. Department of Electrical & Computer Engg, University of Waterloo Department of Electrical & Computer Engg, Waterloo, Ontario, Canada

    Oussama Khatib

  4. Department of Mechanical Systems Enginee, Tokyo University of Agriculture and Tech Department of Mechanical Systems Enginee, Tokyo, Japan

    Gentiane Venture

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Klingbeil, E., Menon, S., Khatib, O. (2017). Experimental Analysis of Human Control Strategies in Contact Manipulation Tasks. In: Kulić, D., Nakamura, Y., Khatib, O., Venture, G. (eds) 2016 International Symposium on Experimental Robotics. ISER 2016. Springer Proceedings in Advanced Robotics, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-319-50115-4_25

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  • DOI: https://doi.org/10.1007/978-3-319-50115-4_25

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