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Proceedings Paper

Landmark-based robust navigation for tactical UGV control in GPS-denied communication-degraded environments
Author(s): Yoichiro Endo; Jonathan C. Balloch; Alexander Grushin; Mun Wai Lee; David Handelman
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Paper Abstract

Control of current tactical unmanned ground vehicles (UGVs) is typically accomplished through two alternative modes of operation, namely, low-level manual control using joysticks and high-level planning-based autonomous control. Each mode has its own merits as well as inherent mission-critical disadvantages. Low-level joystick control is vulnerable to communication delay and degradation, and high-level navigation often depends on uninterrupted GPS signals and/or energy-emissive (non-stealth) range sensors such as LIDAR for localization and mapping. To address these problems, we have developed a mid-level control technique where the operator semi-autonomously drives the robot relative to visible landmarks that are commonly recognizable by both humans and machines such as closed contours and structured lines. Our novel solution relies solely on optical and non-optical passive sensors and can be operated under GPS-denied, communication-degraded environments. To control the robot using these landmarks, we developed an interactive graphical user interface (GUI) that allows the operator to select landmarks in the robot’s view and direct the robot relative to one or more of the landmarks. The integrated UGV control system was evaluated based on its ability to robustly navigate through indoor environments. The system was successfully field tested with QinetiQ North America’s TALON UGV and Tactical Robot Controller (TRC), a ruggedized operator control unit (OCU). We found that the proposed system is indeed robust against communication delay and degradation, and provides the operator with steady and reliable control of the UGV in realistic tactical scenarios.

Paper Details

Date Published: 13 May 2016
PDF: 13 pages
Proc. SPIE 9837, Unmanned Systems Technology XVIII, 98370F (13 May 2016); doi: 10.1117/12.2224231
Show Author Affiliations
Yoichiro Endo, Intelligent Automation, Inc. (United States)
Jonathan C. Balloch, Intelligent Automation, Inc. (United States)
Alexander Grushin, Intelligent Automation, Inc. (United States)
Mun Wai Lee, Intelligent Automation, Inc. (United States)
David Handelman, Intelligent Automation, Inc. (United States)

Published in SPIE Proceedings Vol. 9837:
Unmanned Systems Technology XVIII
Robert E. Karlsen; Douglas W. Gage; Charles M. Shoemaker; Grant R. Gerhart, Editor(s)

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