Extended strong tracking filter SLAM algorithm

Feng Wen*, Xiaojie Chai, Yuan Li, Wei Zou, Kui Yuan

*Corresponding author for this work

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

Abstract

Simultaneous Localization and Mapping (SLAM) is a key issue in robotics community. This paper presents a monocular vision and odometer based SLAM algorithm, making use of a novel artificial landmark which is called MR (Mobile Robot) code. During robot motion, the information from visual observations is fused with that from the odometer by Extended Strong Tracking Filter (STF), which can construct highly accurate maps and locate the robot more accurately than EKF. A new calculation method of suboptimal multiple fading factors is proposed which overcomes the problem of discontinuous observation in normal STF SLAM. Actual experiments are carried out in indoor environment, which shows that the proposed algorithm has improved the localization precision of the robot and the map accuracy.

Original languageEnglish
Title of host publication2011 IEEE International Conference on Mechatronics and Automation, ICMA 2011
Pages1021-1026
Number of pages6
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2011 IEEE International Conference on Mechatronics and Automation, ICMA 2011 - Beijing, China
Duration: 7 Aug 201110 Aug 2011

Publication series

Name2011 IEEE International Conference on Mechatronics and Automation, ICMA 2011

Conference

Conference2011 IEEE International Conference on Mechatronics and Automation, ICMA 2011
Country/TerritoryChina
CityBeijing
Period7/08/1110/08/11

Keywords

  • SLAM
  • artificial landmark
  • mobile robot
  • strong tracking filter

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