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Proceedings Paper

Experimental setup for evaluating an adaptive user interface for teleoperation control
Author(s): Indika B. Wijayasinghe; Srikanth Peetha; Shamsudeen Abubakar; Mohammad Nasser Saadatzi; Sven Cremer; Dan O. Popa
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Paper Abstract

A vital part of human interactions with a machine is the control interface, which single-handedly could define the user satisfaction and the efficiency of performing a task. This paper elaborates the implementation of an experimental setup to study an adaptive algorithm that can help the user better tele-operate the robot. The formulation of the adaptive interface and associate learning algorithms are general enough to apply when the mapping between the user controls and the robot actuators is complex and/or ambiguous. The method uses a genetic algorithm to find the optimal parameters that produce the input-output mapping for teleoperation control. In this paper, we describe the experimental setup and associated results that was used to validate the adaptive interface to a differential drive robot from two different input devices; a joystick, and a Myo gesture control armband. Results show that after the learning phase, the interface converges to an intuitive mapping that can help even inexperienced users drive the system to a goal location.

Paper Details

Date Published: 16 May 2017
PDF: 11 pages
Proc. SPIE 10216, Smart Biomedical and Physiological Sensor Technology XIV, 102160E (16 May 2017); doi: 10.1117/12.2262927
Show Author Affiliations
Indika B. Wijayasinghe, Univ. of Louisville (United States)
Srikanth Peetha, Univ. of Louisville (United States)
Shamsudeen Abubakar, Univ. of Louisville (United States)
Mohammad Nasser Saadatzi, Univ. of Louisville (United States)
Sven Cremer, The Univ. of Texas at Arlington (United States)
Dan O. Popa, Univ. of Louisville (United States)

Published in SPIE Proceedings Vol. 10216:
Smart Biomedical and Physiological Sensor Technology XIV
Brian M. Cullum; Douglas Kiehl; Eric S. McLamore, Editor(s)

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