A Dual Mode Human-Robot Teleoperation Interface Based on Airflow in the Aural Cavity

Author:

Vaidyanathan Ravi1,Fargues Monique P.2,Serdar Kurcan R.2,Gupta Lalit3,Kota Srinivas3,Quinn Roger D.4,Lin Dong5

Affiliation:

1. University of Southampton, Southampton, UK Naval Postgraduate School, Monterey, CA, USA Case Western Reserve University, OH, USA

2. Naval Postgraduate School, Monterey, CA, USA

3. Southern Illinois University, Carbondale, IL, USA

4. Case Western Reserve University, OH, USA

5. Think-A-Move, Ltd, Beachwood, OH, USA

Abstract

Robot teleoperation systems have been limited in their utility due to the need for operator motion, lack of portability and limitation to singular input modalities. In this article, the design and construction of a dual-mode human—machine interface system for robot teleoperation addressing all these issues is presented. The interface is capable of directing robotic devices in response to tongue movement and/or speech without insertion of any device in the vicinity of the oral cavity. The interface is centered on the unique properties of the human ear as an acoustic output device. Specifically, we present: (1) an analysis of the sensitivity of human ear canals as acoustic output device; (2) the design of a new sensor for monitoring airflow in the aural canal; (3) pattern recognition procedures for recognition of both speech and tongue movement by monitoring aural flow across several human test subjects; and (4) a conceptual design and simulation of the machine interface system. We believe this work will lay the foundation for a new generation of human machine interface systems for all manner of robotic applications.

Publisher

SAGE Publications

Subject

Applied Mathematics,Artificial Intelligence,Electrical and Electronic Engineering,Mechanical Engineering,Modeling and Simulation,Software

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Formulation of a new gradient descent MARG orientation algorithm: Case study on robot teleoperation;Mechanical Systems and Signal Processing;2019-09

2. BARTON: Low Power Tongue Movement Sensing with In-Ear Barometers;2017 IEEE 23rd International Conference on Parallel and Distributed Systems (ICPADS);2017-12

3. A heterogeneous framework for real-time decoding of bioacoustic signals: Applications to assistive interfaces and prosthesis control;Expert Systems with Applications;2013-10

4. Pairwise diversity ranking of polychotomous features for ensemble physiological signal classifiers;Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine;2013-04-04

5. Real-time implementation of a non-invasive tongue-based human-robot interface;2010 IEEE/RSJ International Conference on Intelligent Robots and Systems;2010-10

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