Salient Feature of Haptic-Based Guidance of People in Low Visibility Environments Using Hard Reins

Ranasinghe, Anuradha and Sornkarn, Nantachai and Dasgupta, Prokar and Althoefer, Kaspar and Penders, Jacques and Nanayakkara, Thrishantha (2015) Salient Feature of Haptic-Based Guidance of People in Low Visibility Environments Using Hard Reins. IEEE TRANSACTIONS ON CYBERNETICS, 46 (2). pp. 568-579. ISSN PubMed ID: 26080390

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This paper presents salient features of
human–human interaction where 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 salient
features of the interaction between the guider and follower such
as: 1) the order of an autoregressive (AR) control policy that
maps states of the follower to actions of the guider; 2) how
the guider may modulate the pulling force in response to the
trust level of the follower; and 3) how learning may successively
apportion the responsibility of control across different muscles
of the guider. Based on experimental systems identification on
human demonstrations from ten pairs of naive subjects, we
show that guiders tend to adopt a third-order AR predictive
control policy and followers tend to adopt second-order reactive
control policy. Moreover, the extracted guider’s control policy
was implemented and validated by human–robot interaction
experiments. By modeling the follower’s dynamics with a time
varying virtual damped inertial system, we found that it is the
coefficient of virtual damping which is most sensitive to the
trust level of the follower. We used these experimental insights
to derive a novel controller that integrates an optimal order
control policy with a push/pull force modulator in response to
the trust level of the follower monitored using a time varying
virtual damped inertial model.

Item Type: Article
Additional Information and Comments: (c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works."
Faculty / Department: Faculty of Science > Mathematics and Computer Science
Depositing User: Anuradha Dissanayake Mudiyanselage
Date Deposited: 08 Dec 2016 15:46
Last Modified: 05 Mar 2018 01:35

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