13 May 2016 Landmark-based robust navigation for tactical UGV control in GPS-denied communication-degraded environments
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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.
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Yoichiro Endo, Yoichiro Endo, Jonathan C. Balloch, Jonathan C. Balloch, Alexander Grushin, Alexander Grushin, Mun Wai Lee, Mun Wai Lee, David Handelman, David Handelman, "Landmark-based robust navigation for tactical UGV control in GPS-denied communication-degraded environments", Proc. SPIE 9837, Unmanned Systems Technology XVIII, 98370F (13 May 2016); doi: 10.1117/12.2224231; https://doi.org/10.1117/12.2224231


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