Predicting Mobility using Statistics (PreMoStat)
Abstract
The purpose of this project was to develop methods and software to determine whether a given Small Unmanned Ground Vehicle (SUGV) can traverse a given terrain, when both the SUGV and the terrain are not known exactly. A simulation model of a real-world SUGV (iRobot PackBot) was developed in the ADAMS environment and used to simulate traversal of a variable-height step obstacle. For this project, a user subroutine was successfully integrated into the ADAMS model to predict deformable track-terrain interaction. A parameterizable UGV vehicle system model was implemented using the ADAMS command language. A key element of this model is a slip-sinkage model. This simulation model was validated using real-world data collected in a step validation fixture with sand and a variable-height curb. In a related effort, this project developed methods for using UGV sensor data to estimate variables and parameters needed for traction force prediction. The methods were evaluated using data collected from experiments with a PackBot traversing various deformable and non-deformable surfaces.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 10, 2011
- Accession Number
- ADA542362
Entities
People
- Andy Moore
- Douglas D. Hackett
- Eric Krotkov
- Javier Solis
- Raul G. Longoria