Pittiglio, G, Calo, S and Valdastri, P orcid.org/0000-0002-2280-5438 (2020) On the Observability and Observer Design on the Special Orthogonal Group Based on Partial Inertial Sensing. IEEE Transactions on Automatic Control. p. 1. ISSN 0018-9286
Abstract
The aim of the present work is to discuss the observability properties and observer design for the attitude of a rigid body, in conditions of partial inertial sensing. In particular, we introduce an observability analysis tool for the attitude dynamics when only accelerometer and gyroscope measurements are available, as in several robotics applications. In various scenarios, in fact, the measurement of the magnetic field via a magnetometer is unreliable, due to magnetic interferences. Herein, we first focus on a formal observability analysis, which reveals that the target dynamics is weakly locally observable, but not first-order observable. The lack of first-order observability prevents standard observers from achieving global convergence. Therefore, we discuss a more suitable approach for observer design to deal with this problem. The proposed approach is validated by providing numerical and experimental results. The former show that the proposed approach is able to achieve convergence (final error 0.004%). Experiments validate our inference about observability and show the improvements brought by the proposed approach concerning the error convergence (final error 0.15%).
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | Algebraic/geometric methods; Kalman Filtering; Nonlinear Systems; Nonlinear Observability; Robotics |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds) |
Funding Information: | Funder Grant number Royal Society wm150122 |
Depositing User: | Symplectic Publications |
Date Deposited: | 05 Jan 2021 12:20 |
Last Modified: | 05 Jan 2021 22:19 |
Status: | Published online |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Identification Number: | 10.1109/tac.2020.3047553 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:169379 |