Micro Aerial Vehicle Yaw Estimation and Localization Based on Ultrasonic Sensors in Indoor Environment

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

Abstract

This paper addresses the problem of yaw angle estimation and indoor positioning of micro aerial vehicle (MAV) under GPS-free environment and complex electromagnetic interference. A distance-ranging-based approach is proposed to localize MAV. The relation of ultrasonic sensors measurements and MAV position as well as yaw angle is given by establishing a nonlinear, implicit, and piecewise continuous model. Thus, the extended Kalman filter (EKF) is applied to estimate the MAV position and yaw angle according to ultrasonic sensors and inertial measurement unit. Furthermore, a jump filter is introduced to compensate the mutation caused by discontinuity of the model. Simulations are presented and the results show the effectiveness of the algorithm.

Original languageEnglish
Title of host publicationProceedings of the 39th Chinese Control Conference, CCC 2020
EditorsJun Fu, Jian Sun
PublisherIEEE Computer Society
Pages3433-3438
Number of pages6
ISBN (Electronic)9789881563903
DOIs
StatePublished - Jul 2020
Event39th Chinese Control Conference, CCC 2020 - Shenyang, China
Duration: 27 Jul 202029 Jul 2020

Publication series

NameChinese Control Conference, CCC
Volume2020-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference39th Chinese Control Conference, CCC 2020
Country/TerritoryChina
CityShenyang
Period27/07/2029/07/20

Keywords

  • EKF algorithm
  • MAV yaw estimation
  • indoor localization

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