Measurement and Analysis of Granular Soil Beneath Lightweight Robotic Running Gear

Abstract

A simple and efficient methodology to generate a mobility map accounting for two sources of uncertainty, namely measurement errors (RMSE of a Digital Elevation Model) and interpolation error (kriging method) is proposed. This methodology means a general-purpose solution since it works with standard and publicly-available Digital Elevation Models (DEMs). The different regions in the map are classified according to the geometry of the surface (i.e. slope) and the soil type. A novel segmentation-based approach has also been proposed to divide the regions of interest into segments where stationarity is ensured. Finally, an initial investigation has been performed showing the major impact that moisture and vegetation produce on a soil and how that effect may be measured using thermal cameras.

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Document Details

Document Type
Technical Report
Publication Date
Feb 27, 2017
Accession Number
AD1058591

Entities

People

  • Karl Iagnemma

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Human Systems
  • Sensors

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Civil Engineering
  • Collision Avoidance
  • Computational Science
  • Computations
  • Data Science
  • Data Set
  • Data Sets
  • Detectors
  • Digital Data
  • Digital Elevation Models
  • Geographic Information Systems
  • Geometry
  • Ground Vehicles
  • Heat Transfer
  • Image Processing
  • Information Processing
  • Information Science
  • Moisture Content
  • Monte Carlo Method
  • Motion Planning
  • Sampling
  • Surface Temperature
  • Surveys

Readers

  • Approximation Theory.
  • Geotechnical Engineering.
  • Robotics and Automation.

Technology Areas

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