A Method For Unmanned Ground Wheeled Vehicle Mobility Estimation In Stochastic Terrain Conditions.

Methods to improve vehicle mobility of wheeled vehicles have been researched for more than 100 years.  The United States Army began developing Unmanned Ground Vehicles (UGV) in the early 1900’s; TARDEC leads this effort in research and development as the center for manned and unmanned ground vehicle systems.  Concurrently, researchers developed and enhanced ground terrain 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 that can be used on-line (in real time) with respect to stochastic terrain conditions. UGVs require additional enhancement to include on-line mobility estimation since today’s vehicles cannot predict nor anticipate terrain conditions on their own prior to the vehicle traversing those conditions.

This paper analyzes methods that have been 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. Based on this analysis, the paper formulates: (i) Components of agile vehicle dynamics and performance, energy consumption, and vehicle mission fulfillment that should be considered while defining the UGV mobility, (ii) Requirements to develop on-line (real time) mobility criteria in stochastic terrain conditions, and (iii) Terrain characterization and agile vehicle dynamics information that should be gathered to estimate UGV mobility in real time.

This analysis is then used to derive a strategy which can be applied to wheeled vehicles, both manned and unmanned, to develop both off-line and on-line analytical criterion. The on-line mobility estimation enables the UGV to make control changes as the event occur (or before it) rather than after the event, causing the vehicle to then optimize its reaction and regain control.  The derived strategy is then used to develop a comprehensive mobility definition and criterion and, thus, presents a method which can be applied to evaluate and enhance vehicle mobility in stochastic conditions of unmanned wheeled vehicles.