Using Modeling and Simulation to Evaluate Stability and Traction Performance of a Track Laying Robotic Vehicle

Abstract

The objective of this paper will be to describe the computer-based modeling, simulation, and limited field testing effort that has been undertaken to investigate the dynamic performance of an unmanned tracked vehicle system while conducting a full matrix of tests designed to evaluate system shock, vibration, dynamic stability and off road mobility characteristics. In this paper we will describe the multi-body modeling methodology used as well as the characteristic data incorporated to define the models and their subsystems. The analysis undertaken is applying M&S to baseline the dynamic performance of the vehicle, and comparing these results with performance levels recorded for several manned vehicle systems. We will identify the virtual test matrix over which we executed the models. Finally we will describe our efforts to visualize our findings through the use of computer generated animations of the vehicle system negotiating various virtual automotive tests making up the test matrix.

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Document Details

Document Type
Technical Report
Publication Date
Jan 04, 2005
Accession Number
ADA439072

Entities

People

  • Dave D. Gunter
  • David J. Gorsich
  • Kevin Edgar
  • Mike D. Letherwood
  • Wesley W. Bylsma

Organizations

  • Tank-automotive and Armaments Command

Tags

Communities of Interest

  • Autonomy
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Acquisition
  • Computers
  • Control Systems
  • Engineering
  • Engineers
  • Ground Vehicles
  • High Performance Computing
  • Mobility
  • Physics
  • Product Prototyping
  • Shear Strength
  • Shear Stresses
  • Simulations
  • Test And Evaluation
  • Tracked Vehicles
  • Unmanned Vehicles
  • Virtual Prototyping

Fields of Study

  • Engineering

Readers

  • Computational Modeling and Simulation
  • Logistics and Supply Chain Management.
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference
  • Autonomy