Characterization Parameters for a Three Degree of Freedom Mobile Robot

Abstract

Control and Navigation logic was developed for a 3-Degree of Freedom Surf-Zone Robot to assist in the identification and characterization of platform parameters for use in the Shuey Dynamic Model. These parameters included, primarily platform rotational inertia and wheel slip. Data was collected in various track scenarios including benign flat terrain and more complicated beach runs. Track lengths spanned short straight paths of no more than 10 meters to full-run point-to-point autonomous navigation paths of up to 80 meters. The longer runs included turns of up to 180 degrees and terrain inclines of 2 degree or less. As expected the Shuey model proved reliable for short runs of no more than 10 meters. For long length runs in the beach environment the Dynamic Model diverged quickly. This is attributed to, primarily, wheel slip conditions and the fact that the Shuey Model is open loop. Motor current was monitored under load conditions to identify wheel slip and simple algorithms were implemented to account for this with little success. However, closed loop heading input resulted in significant improvement to the model.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2013
Accession Number
ADA620422

Entities

People

  • Jessica L. Fitzgerald

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Accuracy
  • Artificial Satellites
  • Autonomous Navigation
  • Cartesian Coordinates
  • Computer Programming
  • Computers
  • Data Storage Systems
  • Dead Reckoning
  • Department Of Defense
  • Detectors
  • Geometry
  • Global Positioning Systems
  • Guidance
  • Navigation
  • Systems Engineering
  • United States Naval Academy
  • Unmanned Vehicles

Readers

  • Computational Modeling and Simulation
  • Inertial Navigation Systems.
  • Logistics and Supply Chain Management.

Technology Areas

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