Multi- and Hyper-Spectral Sensing for Autonomous Ground Vehicle Navigation

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Description

Robotic vehicles that navigate autonomously are hindered by unnecessary avoidance of soft obstacles, and entrapment by potentially avoidable obstacles. Existing sensing technologies fail to reliably distinguish hard obstacles from soft obstacles, as well as impassable thickets and other sources of entrapment. Automated materials classification through advanced sensing methods may provide a means to identify such obstacles, and from their identity, to determine whether they must be avoided. Multi- and hyper-spectral electro-optic sensors are used in remote sensing applications to classify both man-made and naturally occurring materials on the earth's surface by their reflectance spectra. The applicability of this sensing technology ... continued below

Physical Description

53 pages

Creation Information

FOGLER, ROBERT J. June 1, 2003.

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This report is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 12 times . More information about this report can be viewed below.

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  • Sandia National Laboratories
    Publisher Info: Sandia National Labs., Albuquerque, NM, and Livermore, CA (United States)
    Place of Publication: Albuquerque, New Mexico

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Description

Robotic vehicles that navigate autonomously are hindered by unnecessary avoidance of soft obstacles, and entrapment by potentially avoidable obstacles. Existing sensing technologies fail to reliably distinguish hard obstacles from soft obstacles, as well as impassable thickets and other sources of entrapment. Automated materials classification through advanced sensing methods may provide a means to identify such obstacles, and from their identity, to determine whether they must be avoided. Multi- and hyper-spectral electro-optic sensors are used in remote sensing applications to classify both man-made and naturally occurring materials on the earth's surface by their reflectance spectra. The applicability of this sensing technology to obstacle identification for autonomous ground vehicle navigation is the focus of this report. The analysis is restricted to system concepts in which the multi- or hyper-spectral sensor is on-board the ground vehicle, facing forward to detect and classify obstacles ahead of the vehicle. Obstacles of interest include various types of vegetation, rocks, soils, minerals, and selected man-made materials such as paving asphalt and concrete.

Physical Description

53 pages

Source

  • Other Information: PBD: 1 Jun 2003

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Identifier

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  • Report No.: SAND2003-1980
  • Grant Number: AC04-94AL85000
  • DOI: 10.2172/820893 | External Link
  • Office of Scientific & Technical Information Report Number: 820893
  • Archival Resource Key: ark:/67531/metadc740266

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Creation Date

  • June 1, 2003

Added to The UNT Digital Library

  • Oct. 18, 2015, 6:40 p.m.

Description Last Updated

  • April 11, 2016, 7:56 p.m.

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Citations, Rights, Re-Use

FOGLER, ROBERT J. Multi- and Hyper-Spectral Sensing for Autonomous Ground Vehicle Navigation, report, June 1, 2003; Albuquerque, New Mexico. (digital.library.unt.edu/ark:/67531/metadc740266/: accessed September 20, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.