Using ultrasonic and vision sensors within extended kalman filter for robot navigation

Authors

  • Zhenhe Chen Dept. of ECE, University of Western Ontario, London, Ont. N6A 5B9, Canada
  • Ranga Rodrigo Dept. of ECE, University of Western Ontario, London, Ont. N6A 5B9, Canada
  • Vijay Parsa Dept. of ECE, University of Western Ontario, London, Ont. N6A 5B9, Canada
  • Jagath Samarabandu Dept. of ECE, University of Western Ontario, London, Ont. N6A 5B9, Canada

Keywords:

Computer vision, Kalman filtering, Radio navigation, Sensors, Ultrasonic devices, Finite dimensional system, Navigation problem, Robot navigation, Simultaneous localization and map-building (SLAM)

Abstract

The simultaneous localization and map-building (SLAM) problem of robots with Extended Kalman Filter (EKF) framework were studied. Two types of sensing systems, ultrasound and computer vision, were mounted on the robot to perceive the environment so as to simultaneously localize the robot. The Kalman Filter (KF) is a linear, discrete-time, finite dimensional system with recursive structure that makes a digital computer well suited for its implementation. EKF provides a real-time solution to the navigation problem and to on-going estimation of the uncertainty acquired from vehicle motion and landmark observation.

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Published

2005-09-01

How to Cite

1.
Chen Z, Rodrigo R, Parsa V, Samarabandu J. Using ultrasonic and vision sensors within extended kalman filter for robot navigation. Canadian Acoustics [Internet]. 2005 Sep. 1 [cited 2021 Oct. 26];33(3):28-9. Available from: https://jcaa.caa-aca.ca/index.php/jcaa/article/view/1729

Issue

Section

Proceedings of the Acoustics Week in Canada