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Journal of Field Robotics
Article . 2006 . Peer-reviewed
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Article . 2006
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Article . 2006
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Terrain characterization and classification with a mobile robot

Authors: Ojeda, Lauro; Borenstein, Johann; Witus, Gary; Karlsen, Robert;

Terrain characterization and classification with a mobile robot

Abstract

AbstractThis paper introduces novel methods for terrain classification and characterization with a mobile robot. In the context of this paper,terrain classificationaims at associating terrains with one of a few predefined, commonly known categories, such as gravel, sand, or asphalt.Terrain characterization, on the other hand, aims at determining key parameters of the terrain that affect its ability to support vehicular traffic. Such properties are collectively called “trafficability.” The proposed terrain classification and characterization system comprises a skid‐steer mobile robot, as well as some common and some uncommon but optional onboard sensors. Using these components, our system can characterize and classify terrain in real time and during the robot's actual mission. The paper presents experimental results for both the terrain classification and characterization methods. The methods proposed in this paper can likely also be implemented on tracked robots, although we did not test this option in our work.

Country
United States
Keywords

Engineering, Artificial intelligence for robotics, Mechanical Engineering, Electronic, Electrical & Telecommunications Engineering, Automated systems (robots, etc.) in control theory

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    selected citations
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    155
    popularity
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    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
155
Top 1%
Top 1%
Top 10%
bronze