Mr. Glenn Taylor Profile

Glenn Taylor

Senior Scientist at Soar Technology Inc

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Publications (3)

Proceedings Article | 5 May 2017 Paper

Multi-modal interaction for robotics mules

Glenn Taylor, Michael Quist, Matthew Lanting, Cory Dunham, Paul Muench

Proceedings Volume 10195, 101950T (2017) https://doi.org/10.1117/12.2262896

KEYWORDS: Robotics, Robotic systems, Human-machine interfaces, Speech recognition, Gesture recognition, Sensors, Magnetism, Light sources and illumination, Detection and tracking algorithms, Calibration

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Proceedings Article | 22 May 2015 Paper

Natural interaction for unmanned systems

Glenn Taylor, Ben Purman, Paul Schermerhorn, Guillermo Garcia-Sampedro, Matt Lanting, Michael Quist, Chris Kawatsu

Proceedings Volume 9468, 946805 (2015) https://doi.org/10.1117/12.2180008

KEYWORDS: Unmanned systems, Human-machine interfaces, Sensors, Control systems, Unmanned aerial vehicles, Computing systems, Telecommunications, Video, Gesture recognition, Video surveillance

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Proceedings Article | 22 May 2015 Paper

Multi-modal interaction for UAS control

Glenn Taylor, Ben Purman, Paul Schermerhorn, Guillermo Garcia-Sampedro, Robert Hubal, Kathleen Crabtree, Allen Rowe, Sarah Spriggs

Proceedings Volume 9468, 946802 (2015) https://doi.org/10.1117/12.2180020

KEYWORDS: Control systems, Sensors, Human-machine interfaces, Prototyping, Defense and security, Speech recognition, Intelligence systems, Unmanned systems, Telecommunications, Computer architecture

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Unmanned aircraft systems (UASs) have seen a dramatic increase in military operations over the last two decades. The increased demand for their capabilities on the battlefield has resulted in quick fielding with user interfaces that are designed more for engineers in mind than for UAS operators. UAS interfaces tend to support tele-operation with a joystick or complex, menu-driven interfaces that have a steep learning curve. These approaches to control require constant attention to manage a single UAS and require increased heads-down time in an interface to search for and click on the right menus to invoke commands. The time and attention required by these interfaces makes it difficult to increase a single operator’s span of control to encompass multiple UAS or the control of sensor systems. In this paper, we explore an alternative interface to the standard menu-based control interfaces. Our approach in this work was to first study how operators might want to task a UAS if they were not constrained by a typical menu interface. Based on this study, we developed a prototype multi-modal dialogue interface for more intuitive control of multiple unmanned aircraft and their sensor systems using speech and map-based gesture/sketch. The system we developed is a two-way interface that allows a user to draw on a map while speaking commands to the system, and which provides feedback to the user to ensure the user knows what the system is doing. When the system does not understand the user for some reason – for example, because speech recognition failed or because the user did not provide enough information – the system engages with the user in a dialogue to gather the information needed to perform the command. With the help of UAS operators, we conducted a user study to compare the performance of our prototype system against a representative menu-based control interface in terms of usability, time on task, and mission effectiveness. This paper describes a study to gather data about how people might use a natural interface, the system itself, and the results of the user study. Keywords: UAS control, natural interfaces, multi-modal interaction.

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