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Autonomous Ground Vehicle Terrain Classification Using Internal Sensors

Title: Autonomous Ground Vehicle Terrain Classification Using Internal Sensors.
Name(s): Sadhukhan, Debangshu, author
Moore, Carl, professor directing thesis
Collins, Emmanuel, committee member
Roberts, Rodney, committee member
Department of Mechanical Engineering, degree granting department
Florida State University, degree granting institution
Type of Resource: text
Genre: Text
Issuance: monographic
Date Issued: 2004
Publisher: Florida State University
Florida State University
Place of Publication: Tallahassee, Florida
Physical Form: computer
online resource
Extent: 1 online resource
Language(s): English
Abstract/Description: The semi-autonomous vehicle known as the Experimental Unmanned Vehicle (XUV)was designed by the US Army to autonomously navigate over different types of terrain. The performance of autonomous navigation improves when the vehicle's control system takes into account the type of terrain on which the vehicle is traveling. For example, if the ground is covered with snow a reduction of acceleration is necessary to avoid wheel slip.Previous researchers have developed algorithms based on vision and digital signal processing (DSP) to categorize the traversability of the terrain. Others have used classical terramechanics equations to identify the key terrain parameters. This thesis presents a novel algorithm that uses the vehicle's internal sensors to qualitatively categorize the terrain type in real-time. The algorithm was successful in identifying gravel, packed dirt, and grass.
Identifier: FSU_migr_etd-2115 (IID)
Submitted Note: A Thesis Submitted to the Department of Mechanical Engineering in Partial Fulfillment of the Requirements for the Degree of Master of Science.
Degree Awarded: Spring Semester, 2004.
Date of Defense: March 16, 2004.
Keywords: Terrain Signatures, Probabilistic Neural Network, Pattern Classification, FFT
Bibliography Note: Includes bibliographical references.
Advisory Committee: Carl Moore, Professor Directing Thesis; Emmanuel Collins, Committee Member; Rodney Roberts, Committee Member.
Subject(s): Mechanical engineering
Persistent Link to This Record:
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Host Institution: FSU

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Sadhukhan, D. (2004). Autonomous Ground Vehicle Terrain Classification Using Internal Sensors. Retrieved from