Drone's attitude estimation in corridor-like environments

D. Jano, S. Arogeti

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


In this study, we suggest an attitude estimation algorithm for drones flying indoors. In particular, we consider a corridor-like environment and adapt ideas from the aerospace field, where algorithms were developed for satellite's attitude estimation. Many algorithms can be found that estimate satellite's attitude, based on rate gyroscopes and a sensor called, star-tracker. The star-tracker identifies celestial objects, and by that, determines their directions compared to the satellite. Using star maps, the same celestial objects directions, compared to the earth, is known. By comparing the celestial objects directions in the satellite frame and in the earth frame, the attitude of the satellite can be estimated. Complementing the star-tracker with rate gyroscopes provides smooth attitude estimation, while also compensating for the rate gyroscope's drift. The novelty in this paper comes from the implementation of the star-tracker method on a drone in a corridor-like environment, and by finding features, which replace the celestial objects used by a star-tracker.

Original languageEnglish
Title of host publication2019 European Conference on Mobile Robots, ECMR 2019 - Proceedings
EditorsLibor Preucil, Sven Behnke, Miroslav Kulich
PublisherInstitute of Electrical and Electronics Engineers
ISBN (Electronic)9781728136059
StatePublished - 1 Sep 2019
Event2019 European Conference on Mobile Robots, ECMR 2019 - Prague, Czech Republic
Duration: 4 Sep 20196 Sep 2019

Publication series

Name2019 European Conference on Mobile Robots, ECMR 2019 - Proceedings


Conference2019 European Conference on Mobile Robots, ECMR 2019
Country/TerritoryCzech Republic


  • Corridor-like Environment
  • Drone Attitude Estimation
  • Extended Kalman Filter
  • Quaternion
  • Rate Gyroscopes
  • Vanishing Points

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Optimization
  • Mechanical Engineering


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