Online estimation of geometric and inertia parameters for multirotor aerial vehicles

Valentin Wuest, Vijay Kumar, Giuseppe Loianno

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Accurate knowledge of geometric and inertia parameters are a necessity for precise and robust control of aerial vehicles. We propose a novel filter that is able to fuse motor speed, inertia, and pose measurements to estimate the vehicle's key dynamic properties online. The presented framework is able to estimate the multirotor's moment of inertia, mass, center of mass and each sensor module's relative position. Obtaining these estimates in-flight allow the multirotor to be precisely controlled even during tasks such as load transportation or after configuration changes on scene. We provide a nonlinear observability analysis, proving that the presented model is locally weakly observable. Experimental results validate the proposed approach, showing the ability to estimate the dynamic properties accurately and demonstrate its capability to do so even while additional loads are added. The framework is flexible and can easily be adapted to a wide range of applications, including self-calibration, object grasping, and single robot or multi-robot payload transportation.

Original languageEnglish (US)
Title of host publication2019 International Conference on Robotics and Automation, ICRA 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1884-1890
Number of pages7
ISBN (Electronic)9781538660263
DOIs
StatePublished - May 1 2019
Event2019 International Conference on Robotics and Automation, ICRA 2019 - Montreal, Canada
Duration: May 20 2019May 24 2019

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
Volume2019-May
ISSN (Print)1050-4729

Conference

Conference2019 International Conference on Robotics and Automation, ICRA 2019
CountryCanada
CityMontreal
Period5/20/195/24/19

Fingerprint

Robots
Antennas
Observability
Electric fuses
Robust control
Calibration
Sensors

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

Cite this

Wuest, V., Kumar, V., & Loianno, G. (2019). Online estimation of geometric and inertia parameters for multirotor aerial vehicles. In 2019 International Conference on Robotics and Automation, ICRA 2019 (pp. 1884-1890). [8794274] (Proceedings - IEEE International Conference on Robotics and Automation; Vol. 2019-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICRA.2019.8794274

Online estimation of geometric and inertia parameters for multirotor aerial vehicles. / Wuest, Valentin; Kumar, Vijay; Loianno, Giuseppe.

2019 International Conference on Robotics and Automation, ICRA 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 1884-1890 8794274 (Proceedings - IEEE International Conference on Robotics and Automation; Vol. 2019-May).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wuest, V, Kumar, V & Loianno, G 2019, Online estimation of geometric and inertia parameters for multirotor aerial vehicles. in 2019 International Conference on Robotics and Automation, ICRA 2019., 8794274, Proceedings - IEEE International Conference on Robotics and Automation, vol. 2019-May, Institute of Electrical and Electronics Engineers Inc., pp. 1884-1890, 2019 International Conference on Robotics and Automation, ICRA 2019, Montreal, Canada, 5/20/19. https://doi.org/10.1109/ICRA.2019.8794274
Wuest V, Kumar V, Loianno G. Online estimation of geometric and inertia parameters for multirotor aerial vehicles. In 2019 International Conference on Robotics and Automation, ICRA 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 1884-1890. 8794274. (Proceedings - IEEE International Conference on Robotics and Automation). https://doi.org/10.1109/ICRA.2019.8794274
Wuest, Valentin ; Kumar, Vijay ; Loianno, Giuseppe. / Online estimation of geometric and inertia parameters for multirotor aerial vehicles. 2019 International Conference on Robotics and Automation, ICRA 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 1884-1890 (Proceedings - IEEE International Conference on Robotics and Automation).
@inproceedings{f5a7e04bba4041bd8163f05721c7cbab,
title = "Online estimation of geometric and inertia parameters for multirotor aerial vehicles",
abstract = "Accurate knowledge of geometric and inertia parameters are a necessity for precise and robust control of aerial vehicles. We propose a novel filter that is able to fuse motor speed, inertia, and pose measurements to estimate the vehicle's key dynamic properties online. The presented framework is able to estimate the multirotor's moment of inertia, mass, center of mass and each sensor module's relative position. Obtaining these estimates in-flight allow the multirotor to be precisely controlled even during tasks such as load transportation or after configuration changes on scene. We provide a nonlinear observability analysis, proving that the presented model is locally weakly observable. Experimental results validate the proposed approach, showing the ability to estimate the dynamic properties accurately and demonstrate its capability to do so even while additional loads are added. The framework is flexible and can easily be adapted to a wide range of applications, including self-calibration, object grasping, and single robot or multi-robot payload transportation.",
author = "Valentin Wuest and Vijay Kumar and Giuseppe Loianno",
year = "2019",
month = "5",
day = "1",
doi = "10.1109/ICRA.2019.8794274",
language = "English (US)",
series = "Proceedings - IEEE International Conference on Robotics and Automation",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1884--1890",
booktitle = "2019 International Conference on Robotics and Automation, ICRA 2019",

}

TY - GEN

T1 - Online estimation of geometric and inertia parameters for multirotor aerial vehicles

AU - Wuest, Valentin

AU - Kumar, Vijay

AU - Loianno, Giuseppe

PY - 2019/5/1

Y1 - 2019/5/1

N2 - Accurate knowledge of geometric and inertia parameters are a necessity for precise and robust control of aerial vehicles. We propose a novel filter that is able to fuse motor speed, inertia, and pose measurements to estimate the vehicle's key dynamic properties online. The presented framework is able to estimate the multirotor's moment of inertia, mass, center of mass and each sensor module's relative position. Obtaining these estimates in-flight allow the multirotor to be precisely controlled even during tasks such as load transportation or after configuration changes on scene. We provide a nonlinear observability analysis, proving that the presented model is locally weakly observable. Experimental results validate the proposed approach, showing the ability to estimate the dynamic properties accurately and demonstrate its capability to do so even while additional loads are added. The framework is flexible and can easily be adapted to a wide range of applications, including self-calibration, object grasping, and single robot or multi-robot payload transportation.

AB - Accurate knowledge of geometric and inertia parameters are a necessity for precise and robust control of aerial vehicles. We propose a novel filter that is able to fuse motor speed, inertia, and pose measurements to estimate the vehicle's key dynamic properties online. The presented framework is able to estimate the multirotor's moment of inertia, mass, center of mass and each sensor module's relative position. Obtaining these estimates in-flight allow the multirotor to be precisely controlled even during tasks such as load transportation or after configuration changes on scene. We provide a nonlinear observability analysis, proving that the presented model is locally weakly observable. Experimental results validate the proposed approach, showing the ability to estimate the dynamic properties accurately and demonstrate its capability to do so even while additional loads are added. The framework is flexible and can easily be adapted to a wide range of applications, including self-calibration, object grasping, and single robot or multi-robot payload transportation.

UR - http://www.scopus.com/inward/record.url?scp=85071452455&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85071452455&partnerID=8YFLogxK

U2 - 10.1109/ICRA.2019.8794274

DO - 10.1109/ICRA.2019.8794274

M3 - Conference contribution

T3 - Proceedings - IEEE International Conference on Robotics and Automation

SP - 1884

EP - 1890

BT - 2019 International Conference on Robotics and Automation, ICRA 2019

PB - Institute of Electrical and Electronics Engineers Inc.

ER -