Literature DB >> 29744380

Velocity-curvature patterns limit human-robot physical interaction.

Pauline Maurice1, Meghan E Huber2, Neville Hogan2, Dagmar Sternad3.   

Abstract

Physical human-robot collaboration is becoming more common, both in industrial and service robotics. Cooperative execution of a task requires intuitive and efficient interaction between both actors. For humans, this means being able to predict and adapt to robot movements. Given that natural human movement exhibits several robust features, we examined whether human-robot physical interaction is facilitated when these features are considered in robot control. The present study investigated how humans adapt to biological and non-biological velocity patterns in robot movements. Participants held the end-effector of a robot that traced an elliptic path with either biological (two-thirds power law) or non-biological velocity profiles. Participants were instructed to minimize the force applied on the robot end-effector. Results showed that the applied force was significantly lower when the robot moved with a biological velocity pattern. With extensive practice and enhanced feedback, participants were able to decrease their force when following a non-biological velocity pattern, but never reached forces below those obtained with the 2/3 power law profile. These results suggest that some robust features observed in natural human movements are also a strong preference in guided movements. Therefore, such features should be considered in human-robot physical collaboration.

Entities:  

Keywords:  Human Factors and Human-in-the-Loop; Human-Centered Robotics; Physical Human-Robot Interaction

Year:  2017        PMID: 29744380      PMCID: PMC5937985          DOI: 10.1109/LRA.2017.2737048

Source DB:  PubMed          Journal:  IEEE Robot Autom Lett


  16 in total

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  7 in total

1.  Stability and Predictability in Dynamically Complex Physical Interactions.

Authors:  Salah Bazzi; Julia Ebert; Neville Hogan; Dagmar Sternad
Journal:  IEEE Int Conf Robot Autom       Date:  2018-09-13

2.  Dynamic Primitives Limit Human Force Regulation during Motion.

Authors:  A Michael West; James Hermus; Meghan E Huber; Pauline Maurice; Dagmar Sternad; Neville Hogan
Journal:  IEEE Robot Autom Lett       Date:  2022-01-11

3.  Inherent Kinematic Features of Dynamic Bimanual Path Following Tasks.

Authors:  Jacob R Boehm; Nicholas P Fey; Ann Majewicz
Journal:  IEEE Trans Hum Mach Syst       Date:  2020-09-15       Impact factor: 4.124

4.  Separating neural influences from peripheral mechanics: the speed-curvature relation in mechanically constrained actions.

Authors:  James Hermus; Joseph Doeringer; Dagmar Sternad; Neville Hogan
Journal:  J Neurophysiol       Date:  2020-03-11       Impact factor: 2.714

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Authors:  Salah Bazzi; Dagmar Sternad
Journal:  Adv Robot       Date:  2020-06-16       Impact factor: 1.699

6.  Robustness in Human Manipulation of Dynamically Complex Objects through Control Contraction Metrics.

Authors:  Salah Bazzi; Dagmar Sternad
Journal:  IEEE Robot Autom Lett       Date:  2020-02-10

7.  Optimal Biomechanical Performance in Upper-Limb Gestures Depends on Velocity and Carried Load.

Authors:  Cristina Brambilla; Matteo Malosio; Gianluigi Reni; Alessandro Scano
Journal:  Biology (Basel)       Date:  2022-03-02
  7 in total

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