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- W4252134619 abstract "In this paper, we present <i>Argos</i>, an autonomous ground robot built for the 2009 Intelligent Ground Vehicle Competition (IGVC). Discussed are the significant improvements over its predecessor from the 2008 IGVC, <i>Kratos</i>. We continue to use stereo vision techniques to generate a cost map of the environment around the robot. Lane detection is improved through the use of color filters that are robust to changing lighting conditions. The addition of a single-axis gyroscope to the sensor suite allows accurate measurement of the robot's yaw rate and compensates for wheel slip, vastly improving state estimation. The combination of the D* Lite algorithm, which avoids unnecessary re-planning, and the Field D* algorithm, which allows us to plan much smoother paths, results in an algorithm that produces higher quality paths in the same amount of time as methods utilizing A*. The successful implementation of a crosstrack error navigation law allows the robot to follow planned paths without cutting corners, reducing the chance of collision with obstacles. A redesigned chassis with a smaller footprint and a bi-level design, combined with a more powerful drivetrain, makes <i>Argos</i> much more agile and maneuverable compared to its predecessor. At the 2009 IGVC, Argos placed first in the Navigation Challenge." @default.
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- W4252134619 date "2010-01-17" @default.
- W4252134619 modified "2023-10-16" @default.
- W4252134619 title "Argos: Princeton University's entry in the 2009 Intelligent Ground Vehicle Competition" @default.
- W4252134619 doi "https://doi.org/10.1117/12.839125" @default.
- W4252134619 hasPublicationYear "2010" @default.
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