University of Illinois Urbana-Champaign

Hardware and software considerations for monocular SLAM in a riverine environment

Miller, Martin Hudson

Content Files
MILLER-THESIS-2017.pdf

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https://hdl.handle.net/2142/99412

Description

Title
Hardware and software considerations for monocular SLAM in a riverine environment
Author(s)
Miller, Martin Hudson
Issue Date
2017-12-12
Director of Research (if dissertation) or Advisor (if thesis)
  • Hutchinson, Seth A.
  • Chung, Soon-Jo
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Date of Ingest
2018-03-13T15:49:12Z
Keyword(s)
  • Simultaneous localization and mapping (SLAM)
  • Monocular
  • Stereo
  • River
  • Inertial measurement unit (IMU)
  • Camera
  • Robotics
  • Inertial
Abstract
A monocular SLAM algorithm for use on rivers is proposed and compared to existing methods using a newly created SLAM dataset. The proposed algorithm uses a single camera and inertial measurements to estimate the location of a canoe and a map of a river simultaneously using an extended Kalman filter. The algorithm exploits the reflections of map landmarks in the river in order to obtain a depth estimate from a single view. Landmark reflections are found by using the state covariance matrix of the extended Kalman filter to define a search region where reflections are likely to be found. A process noise model is proposed to more accurately reflect the noise characteristics of the inertial measurement unit. The dataset used for the experiments was collected from a canoe on the Sangamon River covering 2.7 kilometers in 44 minutes and divided into eight subsets. Data collected includes stereo images, inertial measurements, and GPS position data for ground truth. The proposed algorithm is evaluated by measuring the translation and attitude error with respect to ground truth and comparisons are made to the stereo method, ORB-SLAM2.
Graduation Semester
2017-12
Type of Resource
text
Permalink
http://hdl.handle.net/2142/99412
Copyright and License Information
Copyright 2017 Martin Miller

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