Literature DB >> 27788067

Physical Collaboration of Human-Human and Human-Robot Teams.

K B Reed, M A Peshkin.   

Abstract

Human partners working on a target acquisition task perform faster than do individuals on the same task, even though the partners consider each other to be an impediment. We recorded the force profile of each partner during the task, revealing an emergent specialization of roles that could only have been negotiated through a haptic channel. With this understanding of human haptic communication we attempted a "haptic Turing test," replicating human behaviors in a robot partner. Human participants consciously and incorrectly believed their partner was human. However, force profiles did not show specialization of roles in the human partner, nor enhanced dyadic performance, suggesting that haptic interaction holds a greater subconscious subtlety. We further report observations of a non-zero dyadic steady state force perhaps analogous to co-contraction within the limb of an individual, where it contributes to limb stiffness and disturbance rejection. We present results on disturbance rejection in a dyad, showing lack of an effective dyadic strategy for brief events.

Entities:  

Year:  2008        PMID: 27788067     DOI: 10.1109/TOH.2008.13

Source DB:  PubMed          Journal:  IEEE Trans Haptics        ISSN: 1939-1412            Impact factor:   2.487


  27 in total

1.  For Motion Assistance Humans Prefer to Rely on a Robot Rather Than on an Unpredictable Human.

Authors:  Ekaterina Ivanova; Gerolamo Carboni; Jonathan Eden; Jorg Kruger; Etienne Burdet
Journal:  IEEE Open J Eng Med Biol       Date:  2020-04-16

2.  Performance drifts in two-finger cyclical force production tasks performed by one and two actors.

Authors:  Fariba Hasanbarani; Sasha Reschechtko; Mark L Latash
Journal:  Exp Brain Res       Date:  2018-01-15       Impact factor: 1.972

3.  Velocity-curvature patterns limit human-robot physical interaction.

Authors:  Pauline Maurice; Meghan E Huber; Neville Hogan; Dagmar Sternad
Journal:  IEEE Robot Autom Lett       Date:  2017-08-09

4.  Motion Plan Changes Predictably in Dyadic Reaching.

Authors:  Atsushi Takagi; Niek Beckers; Etienne Burdet
Journal:  PLoS One       Date:  2016-12-02       Impact factor: 3.240

5.  On the Role of Physical Interaction on Performance of Object Manipulation by Dyads.

Authors:  Keivan Mojtahedi; Qiushi Fu; Marco Santello
Journal:  Front Hum Neurosci       Date:  2017-11-07       Impact factor: 3.169

6.  Communication and Inference of Intended Movement Direction during Human-Human Physical Interaction.

Authors:  Keivan Mojtahedi; Bryan Whitsell; Panagiotis Artemiadis; Marco Santello
Journal:  Front Neurorobot       Date:  2017-04-13       Impact factor: 2.650

7.  Competitive and cooperative arm rehabilitation games played by a patient and unimpaired person: effects on motivation and exercise intensity.

Authors:  Maja Goršič; Imre Cikajlo; Domen Novak
Journal:  J Neuroeng Rehabil       Date:  2017-03-23       Impact factor: 4.262

8.  Small forces that differ with prior motor experience can communicate movement goals during human-human physical interaction.

Authors:  Andrew Sawers; Tapomayukh Bhattacharjee; J Lucas McKay; Madeleine E Hackney; Charles C Kemp; Lena H Ting
Journal:  J Neuroeng Rehabil       Date:  2017-01-31       Impact factor: 4.262

9.  A framework to describe, analyze and generate interactive motor behaviors.

Authors:  Nathanaël Jarrassé; Themistoklis Charalambous; Etienne Burdet
Journal:  PLoS One       Date:  2012-11-30       Impact factor: 3.240

10.  Force sharing and other collaborative strategies in a dyadic force perception task.

Authors:  Fabio Tatti; Gabriel Baud-Bovy
Journal:  PLoS One       Date:  2018-02-23       Impact factor: 3.240

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