Trafficability and Mobility Analysis from Remote Sensing

Abstract

The Grant work consists of determining the effectiveness of newly collected libraries and developed models by test and evaluation with a range of remotely sensed data. The project will 1) expand the model applicability to soil types and conditions, relevant to beach landing zones, egress routes, and inland mobility, including, specifically, soils of low mobility (wet/saturated clays and mixtures); 2) develop models and methods and evaluate applicability of hyperspectral image (HSI) and multispectral image (MSI) sensor integration on unmanned and manned vehicles for rapid, in route, trafficability estimates; 3) evaluate improved models for retrieval of trafficability from airborne assets such as airborne hyperspectral and multispectral imagery from conventional aircraft and UAV platforms as well as satellite sensors such as Worldview-3 and Worldview-2; and 4) integrate the mobility models into the HSI-to-mobility prediction data flow.

Document Details

Document Type
DoD Grant Award
Publication Date
May 19, 2016
Source ID
N00173151G904

Entities

People

  • Charles Bachmann

Organizations

  • Rochester Institute of Technology
  • United States Naval Research Laboratory
  • United States Navy

Tags

Readers

  • Computational Modeling and Simulation
  • Computer Vision.
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

  • Autonomy
  • Space