Salient features of haptic based guidance of people with limited vision using hard reins

RANASINGHE, Anuradha, SORNKARN, Nantachai, DASGUPTA, Prokar, ALTHOEFER, Kaspar, PENDERS, Jacques and NANAYAKKARA, Thrishantha (2015). Salient features of haptic based guidance of people with limited vision using hard reins. IEEE Transactions on cybernetics, 46 (2), 568-579.

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Link to published version:: 10.1109/TCYB.2015.2409772

Abstract

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 the follower such as a) the order of an autoregressive control policy that maps states of the follower to actions of the guider, b) how the guider may modulate the pulling force in response to the confidence level of the follower, and c) 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 3rd order auto-regressive predictive control policy and followers tend to adopt 2nd 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 confidence 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 confidence level of the follower monitored using a time varying virtual damped inertial model.

Item Type: Article
Research Institute, Centre or Group: Materials and Engineering Research Institute > Centre for Automation and Robotics Research > Mobile Machine and Vision Laboratory
Identification Number: 10.1109/TCYB.2015.2409772
Depositing User: Jacques Penders
Date Deposited: 01 Mar 2016 10:02
Last Modified: 20 Oct 2016 22:01
URI: http://shura.shu.ac.uk/id/eprint/11593

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