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Indices and Computational Strategy for Unmanned Ground Wheeled Vehicle Mobility Estimation and Enhancement

[+] Author Affiliations
Jeremy P. Gray, Jim L. Overholt

US Army TARDEC, Warren, MI

Vladimir V. Vantsevich

The University of Alabama at Birmingham, Birmingham, AL

Paper No. DETC2013-12158, pp. V06AT07A068; 10 pages
doi:10.1115/DETC2013-12158
From:
  • ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 6A: 37th Mechanisms and Robotics Conference
  • Portland, Oregon, USA, August 4–7, 2013
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5593-5
  • Copyright © 2013 by ASME

abstract

The United States Army began developing Unmanned Ground Vehicles (UGV) in the early 1900’s. Concurrently, researchers developed and enhanced passenger and commercial ground vehicles. Although significant progress has been made for improving vehicle mobility for all ground vehicles throughout the past century, mobility has lacked a concise mutually agreed definition and analytical standardized criteria. The implementations of improved technologies, such as vehicle traction control, stability control, and torque vectoring systems require researchers to take a step back and reevaluate mobility criteria. UGVs require additional enhancement to include on-line mobility estimation since the vehicle cannot predict nor anticipate terrain conditions on their own prior to the vehicle traversing those conditions.

This paper analyzes methodologies researchers have employed for defining and improving vehicle mobility of wheeled vehicles. The analysis is done from a view point of concurrent mobility methodologies’ enhancement and applicability to wheeled UGVs.

This analysis is then used to develop off-line and on-line analytical criterion for mobility estimation, and to derive a strategy which can be applied to wheeled vehicles, both manned and unmanned. The on-line mobility estimation enables the UGV to make control changes as the events occur rather than after the event, causing the vehicle to then optimize its reaction to regain control.

Copyright © 2013 by ASME
Topics: Vehicles

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