Model Predictive Control for Uncalibrated Visual Servoing Based on Broyden Estimation

Ning Han, Xuemei Ren*, Dongdong Zheng

*Corresponding author for this work

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

Abstract

The development of machine vision and related technologies in recent years has led to a widespread use of visual servoing in robotics. However, obtaining accurate parameters of camera and robot often necessitates a complex calibration process, making the determination of the projection relationship between image changes and robot joint movements a laborious undertaking. In order to solve the problem, Broyden estimation is applied in this paper to estimate the combined Jacobian matrix online, and the estimation results are then introduced into a model predictive controller to solve the dynamic visual tracking problem, while the constraints of joint angles and velocities are considered. The simulation results verify the effectiveness of the proposed algorithm.

Original languageEnglish
Title of host publicationProceedings of 2023 Chinese Intelligent Systems Conference - Volume III
EditorsYingmin Jia, Weicun Zhang, Yongling Fu, Jiqiang Wang
PublisherSpringer Science and Business Media Deutschland GmbH
Pages441-450
Number of pages10
ISBN (Print)9789819968855
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event19th Chinese Intelligent Systems Conference, CISC 2023 - Ningbo, China
Duration: 14 Oct 202315 Oct 2023

Publication series

NameLecture Notes in Electrical Engineering
Volume1091 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference19th Chinese Intelligent Systems Conference, CISC 2023
Country/TerritoryChina
CityNingbo
Period14/10/2315/10/23

Keywords

  • Broyden estimation
  • Combined jacobian
  • Model predictive control
  • Visual servoing

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