Sliding mode three-dimension SLAM with application to quadrotor helicopter

Salvador Ortiz Santos, Wen Yu, Erik Zamora

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

3 Scopus citations

Abstract

Unmanned Aerial Vehicles (UAV) systems have increased their applications, however, in different environments, it is not possible to obtain the location with devices such as the Global Positioning System (GPS). Also, in exploration applications, it is required to build maps with these systems. In this paper, the navigation of a quadcopter is carried out where an algorithm is proposed to solve the Simultaneous Localization And Mapping (SLAM) problem. Therefore, the Extended Kalman Filter (EKF) is one of the most used techniques to perform SLAM in different robots. However, one of the restrictions of the EKF asks that the uncertainties must be of the Gaussian type wirh zero-mean. For this reason, we propose the SM-SLAM algorithm to relax this restriction, in such a way, the algorithm is robust against bounded perturbations. The results obtained from the proposed algorithm are compared with the EKF-SLAM.

Original languageEnglish
Title of host publication2018 15th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538670323
DOIs
StatePublished - 13 Nov 2018
Externally publishedYes
Event15th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2018 - Mexico City, Mexico
Duration: 5 Sep 20187 Sep 2018

Publication series

Name2018 15th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2018

Conference

Conference15th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2018
Country/TerritoryMexico
CityMexico City
Period5/09/187/09/18

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