Stability and Robustness Analysis Tools for Marine Robot Localization and Mapping Applications

Abstract

The aim of this analysis is to explore the fundamental stability issues of a robotic vehicle carrying out localization, mapping, and feedback control in a perturbation-filled environment. Motivated by the application of an ocean vehicle performing an autonomous ship hull inspection, a planar vehicle model performs localization using point features from a given map. Cases in which the agent must update the map are also considered. The stability of the marine robot controller and estimator duo is investigated using a pair of theorems requiring boundedness and convergence of the transition matrix Euclidean norm. These theorems yield a stability test for the feedback controller. Perturbations are then considered using a theorem on the convergence on the perturbed system transition matrix, yielding a robustness test for the estimator. Together, these tests form a set of tools which can be used in planning and evaluating the robustness of marine vehicle survey trajectories, which is demonstrated through experiment.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2009
Accession Number
ADA507889

Entities

People

  • Brendan J. Englot

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Autonomy
  • Ground and Sea Platforms
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Autonomous Underwater Vehicles
  • Autonomous Vehicles
  • Computational Complexity
  • Differential Equations
  • Geometry
  • Kalman Filters
  • Mathematical Filters
  • Mechanical Engineering
  • Motion Planning
  • Robots
  • Simultaneous Localization And Mapping
  • Three Dimensional
  • Time Intervals
  • Two Dimensional
  • Unmanned Vehicles

Readers

  • Mathematical Modeling and Probability Theory.
  • Naval Architecture and Marine Engineering.
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Autonomy - Autonomous System Control