contributor author | Lines, Austin P. | |
contributor author | Elliott, Joshua J. | |
contributor author | Ray, Laura E. | |
date accessioned | 2023-08-16T18:30:49Z | |
date available | 2023-08-16T18:30:49Z | |
date copyright | 1/13/2023 12:00:00 AM | |
date issued | 2023 | |
identifier issn | 2690-702X | |
identifier other | javs_2_3_031001.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4292069 | |
description abstract | This article presents a new method of detecting incipient immobilization for a wheeled mobile robot operating in deformable terrain with high spatial variability. This approach uses proprioceptive sensor data from a four-wheeled, rigid chassis rover operating in poorly bonded, compressible snow to develop canonic, dynamical system models of robot’s operation. These serve as hypotheses in a multiple model estimation algorithm used to predict the robot’s mobility in real time. This prediction method eliminates the need for choosing an empirical wheel–terrain interaction model, determining terramechanics parameter values, or for collecting large training datasets needed for machine learning classification. When tested on field data, this new method warns of decreased mobility an average of 1.8 m and 2.9 s before the rover is completely immobilized. This system also proves to be a reliable predictor of immobilization when evaluated in simulated scenarios of rovers with passive suspension maneuvering in more variable terrain. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Incipient Immobilization Detection for Lightweight Rovers Operating in Deformable Terrain | |
type | Journal Paper | |
journal volume | 2 | |
journal issue | 3 | |
journal title | Journal of Autonomous Vehicles and Systems | |
identifier doi | 10.1115/1.4056408 | |
journal fristpage | 31001-1 | |
journal lastpage | 31001-15 | |
page | 15 | |
tree | Journal of Autonomous Vehicles and Systems:;2023:;volume( 002 ):;issue: 003 | |
contenttype | Fulltext | |