Identification of Haptic Based Guiding Using Hard Reins.
File(s)
Accepted version
Published version
Author(s)
Ranasinghe, A
Dasgupta, P
Althoefer, K
Nanayakkara, T
Type
Journal Article
Abstract
This paper presents identifications of human-human interaction in which one person with limited auditory and visual perception of the environment (a follower) is guided by an agent with full perceptual capabilities (a guider) via a hard rein along a given path. We investigate several identifications of the interaction between the guider and the follower such as computational models that map states of the follower to actions of the guider and the computational basis of the guider to modulate the force on the rein in response to the trust level of the follower. Based on experimental identification systems on human demonstrations show that the guider and the follower experience learning for an optimal stable state-dependent novel 3rd and 2nd order auto-regressive predictive and reactive control policies respectively. By modeling the follower's dynamics using a time varying virtual damped inertial system, we found that the coefficient of virtual damping is most appropriate to explain the trust level of the follower at any given time. Moreover, we present the stability of the extracted guiding policy when it was implemented on a planar 1-DoF robotic arm. Our findings provide a theoretical basis to design advanced human-robot interaction algorithms applicable to a variety of situations where a human requires the assistance of a robot to perceive the environment.
Date Issued
2015-07-22
Date Acceptance
2015-06-09
Start Page
e0132020
Journal / Book Title
PLoS One
Volume
10
Issue
7
Copyright Statement
: © 2015 Ranasinghe et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any
medium, provided the original author and source are
credited
access article distributed under the terms of the
Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any
medium, provided the original author and source are
credited
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/26201076
PONE-D-14-33768
Subjects
Algorithms
Auditory Perception
Humans
Interpersonal Relations
Models, Theoretical
Robotics
Visual Perception
MD Multidisciplinary
General Science & Technology
Publication Status
Published online
Coverage Spatial
United States