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Proceedings Paper

Visual and tactile interfaces for bi-directional human robot communication
Author(s): Daniel Barber; Stephanie Lackey; Lauren Reinerman-Jones; Irwin Hudson
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Paper Abstract

Seamless integration of unmanned and systems and Soldiers in the operational environment requires robust communication capabilities. Multi-Modal Communication (MMC) facilitates achieving this goal due to redundancy and levels of communication superior to single mode interaction using auditory, visual, and tactile modalities. Visual signaling using arm and hand gestures is a natural method of communication between people. Visual signals standardized within the U.S. Army Field Manual and in use by Soldiers provide a foundation for developing gestures for human to robot communication. Emerging technologies using Inertial Measurement Units (IMU) enable classification of arm and hand gestures for communication with a robot without the requirement of line-of-sight needed by computer vision techniques. These devices improve the robustness of interpreting gestures in noisy environments and are capable of classifying signals relevant to operational tasks. Closing the communication loop between Soldiers and robots necessitates them having the ability to return equivalent messages. Existing visual signals from robots to humans typically require highly anthropomorphic features not present on military vehicles. Tactile displays tap into an unused modality for robot to human communication. Typically used for hands-free navigation and cueing, existing tactile display technologies are used to deliver equivalent visual signals from the U.S. Army Field Manual. This paper describes ongoing research to collaboratively develop tactile communication methods with Soldiers, measure classification accuracy of visual signal interfaces, and provides an integration example including two robotic platforms.

Paper Details

Date Published: 17 May 2013
PDF: 11 pages
Proc. SPIE 8741, Unmanned Systems Technology XV, 87410U (17 May 2013); doi: 10.1117/12.2015956
Show Author Affiliations
Daniel Barber, Univ. of Central Florida (United States)
Stephanie Lackey, Univ. of Central Florida (United States)
Lauren Reinerman-Jones, Univ. of Central Florida (United States)
Irwin Hudson, U.S. Army Research Lab. (United States)


Published in SPIE Proceedings Vol. 8741:
Unmanned Systems Technology XV
Robert E. Karlsen; Douglas W. Gage; Charles M. Shoemaker; Grant R. Gerhart, Editor(s)

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