Please use this identifier to cite or link to this item: https://hdl.handle.net/11681/8590
Title: Mobility performance algorithms for small unmanned ground vehicles
Authors: United States. Army Research, Development, and Engineering Command.
Cold Regions Research and Engineering Laboratory (U.S.)
Richmond, Paul W.
Mason, George L.
Coutermarsh, Barry A.
Pusey, Jason.
Moore, Victoria D.
Keywords: Mobility
Mobility modeling
Modeling and simulation
SUGV
Tractive-force relationship
Unmanned vehicle
Unmanned vehicle performance
Trafficability
Issue Date: May-2009
Publisher: Geotechnical and Structures Laboratory (U.S.)
Engineer Research and Development Center (U.S.)
Series/Report no.: ERDC TR ; 09-6.
Description: Technical Report
Abstract: Future Combat Systems will include Small Unmanned Ground Vehicles (SUGV). Several have already been deployed, including the TALON®, an 80-lb SUGV; PackBot® at 50 lb, and GatorTM at 2500 lb. As doctrine, tactics, techniques, and procedures continue to evolve, there exists a need to represent the performance of these vehicles in Army models and simulations. Army simulations such as COMBATXXI and OneSAF will use the Standard Mobility Application Programmers Interface (STNDMob API) for estimating vehicle performance. Currently, only the Gator can be represented by a STNDMob vehicle class, and it is modeled as a manned vehicle. This report describes the results of a study undertaken to identify and discuss mobility performance algorithms applicable to SUGV in the weight range of 10 to 5000 lb. Algorithms used by the NATO Reference Mobility Model and the STNDMob were examined. Most of the algorithms currently used in STNDMob were found to be applicable to SUGV. However, it was found that vehicle performance data and algorithms for additional material surfaces and obstacles need to be developed; specifically, models and data for wheeled vehicle skid steering, interior building floor and roof surfaces, and stair climbing are needed. Previously unreported SUGV test results for TALON, MATILDA, and PackBot are presented, and performance estimates described herein compared well using currently available algorithms in STNDMob. Recommendations for new algorithms and improvements to current mobility algorithms are presented.
URI: http://hdl.handle.net/11681/8590
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