Nonlinear tracking control for image-based visual servoing with uncalibrated stereo cameras

Siqi Li, Xuemei Ren*, Yuan Li, Haoxuan Qiu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper considers the problem of uncertain camera pose and camera parameters for a 3-degree-of-freedom (DOF) robot manipulator in nonlinear visual servoing tracking control. To solve this problem, the typical Kalman filter (KF) algorithm is designed to estimate the image Jacobian matrix online, which can reduce the system noises to improve the robustness of the control system. Visual optimal feedback controller is developed to precisely track the desired position of the robot manipulator. In addition, stereo cameras are incorporated into the robot manipulator system such that the tracking errors in both camera image frame and robot base frame can simultaneously converge to zero. Experimental results are included to illustrate the effectiveness of the proposed approach.

Original languageEnglish
Title of host publicationProceedings of 2017 Chinese Intelligent Systems Conference
EditorsWeicun Zhang, Junping Du, Yingmin Jia
PublisherSpringer Verlag
Pages333-341
Number of pages9
ISBN (Print)9789811064982
DOIs
Publication statusPublished - 2018
EventChinese Intelligent Systems Conference, CISC 2017 - Mudanjiang, China
Duration: 14 Oct 201715 Oct 2017

Publication series

NameLecture Notes in Electrical Engineering
Volume460
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

ConferenceChinese Intelligent Systems Conference, CISC 2017
Country/TerritoryChina
CityMudanjiang
Period14/10/1715/10/17

Keywords

  • Image jacobian
  • Kalman filter
  • Robot manipulator
  • Visual servoing

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