Tracking control of mobile robots localized via chained fusion of discrete and continuous epipolar geometry, IMU and odometry

David Tick, Aykut C. Satici, Jinglin Shen, Nicholas Gans

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

This paper presents a novel navigation and control system for autonomous mobile robots that includes path planning, localization, and control. A unique vision-based pose and velocity estimation scheme utilizing both the continuous and discrete forms of the Euclidean homography matrix is fused with inertial and optical encoder measurements to estimate the pose, orientation, and velocity of the robot and ensure accurate localization and control signals. A depth estimation system is integrated in order to overcome the loss of scale inherent in vision-based estimation. A path following control system is introduced that is capable of guiding the robot along a designated curve. Stability analysis is provided for the control system and experimental results are presented that prove the combined localization and control system performs with high accuracy.

Original languageEnglish
Pages (from-to)1237-1250
Number of pages14
JournalIEEE Transactions on Cybernetics
Volume43
Issue number4
DOIs
StatePublished - Aug 2013

Keywords

  • Kalman filters
  • Mobile robots
  • Robot control
  • Robot sensing systems
  • Sensor fusion

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