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Probabilistic modeling for positioning applications using inertial sensors
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2014 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

In this thesis, we consider the problem of estimating position and orientation (6D pose) using inertial sensors (accelerometers and gyroscopes). Inertial sensors provide information about the change in position and orientation at high sampling rates. However, they suffer from integration drift and hence need to be supplemented with additional sensors. To combine information from the inertial sensors with information from other sensors we use probabilistic models, both for sensor fusion and for sensor calibration.

Inertial sensors can be supplemented with magnetometers, which are typically used to provide heading information. This relies on the assumption that the measured magnetic field is equal to a constant local magnetic field and that the magnetometer is properly calibrated. However, the presence of metallic objects in the vicinity of the sensor will make the first assumption invalid. If the metallic object is rigidly attached to the sensor, the magnetometer can be calibrated for the presence of this magnetic disturbance. Afterwards, the measurements can be used for heading estimation as if the disturbance was not present. We present a practical magnetometer calibration algorithm that is experimentally shown to lead to improved heading estimates. An alternative approach is to exploit the presence of magnetic disturbances in indoor environments by using them as a source of position information. We show that in the vicinity of a magnetic coil it is possible to obtain accurate position estimates using inertial sensors, magnetometers and knowledge of the magnetic field induced by the coil.

We also consider the problem of estimating a human body’s 6D pose. For this, multiple inertial sensors are placed on the body. Information from the inertial sensors is combined using a biomechanical model which represents the human body as consisting of connected body segments. We solve this problem using an optimization-based approach and show that accurate 6D pose estimates are obtained. These estimates accurately represent the relative position and orientation of the human body, i.e. the shape of the body is accurately represented but the absolute position can not be determined.

To estimate absolute position of the body, we consider the problem of indoor positioning using time of arrival measurements from an ultra-wideband (uwb) system in combination with inertial measurements. Our algorithm uses a tightlycoupled sensor fusion approach and is shown to lead to accurate position and orientation estimates. To be able to obtain position information from the uwb measurements, it is imperative that accurate estimates of the receivers’ positions and clock offsets are known. Hence, we also present an easy-to-use algorithm to calibrate the uwb system. It is based on a maximum likelihood formulation and represents the uwb measurements assuming a heavy-tailed asymmetric noise distribution to account for measurement outliers.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2014. , 50 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1656
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-106882DOI: 10.3384/lic.diva-106882Local ID: LIU-TEK-LIC-2014:89ISBN: 978-91-7519-341-0 (print)OAI: oai:DiVA.org:liu-106882DiVA: diva2:719206
Presentation
2014-06-05, Visionen, B-building, Campus Valla, Linköpings universitet, Linköping, 13:15 (English)
Opponent
Supervisors
Available from: 2014-05-23 Created: 2014-05-23 Last updated: 2016-12-15Bibliographically approved
List of papers
1. Magnetometer calibration using inertial sensors
Open this publication in new window or tab >>Magnetometer calibration using inertial sensors
2016 (English)In: IEEE Sensors Journal, ISSN 1530-437X, E-ISSN 1558-1748, Vol. 16, no 14, 5679-5689 p.Article in journal (Refereed) Published
Abstract [en]

In this work we present a practical calibration algorithm that calibrates a magnetometer using inertial sensors. The calibration corrects for magnetometer sensor errors, for the presence of magnetic disturbances and for misalignment between the magnetometer and the inertial sensor axes. It is based on a maximum likelihood formulation and is formulated as an offline method. It is shown to give good results using data from two different commercially available sensor units. Using the calibrated magnetometer measurements in combination with the inertial sensors to determine orientation, is shown to lead to significantly improved heading estimates.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2016
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-106879 (URN)10.1109/JSEN.2016.2569160 (DOI)000379601600024 ()
Note

Funding agencies: Funding Agencies|CADICS; Project Probabilistic Modeling of Dynamical Systems through the Swedish Research Council (Vetenskapsradet) [621-2013-5524]; MC Impulse through the European Commission Seventh Framework Programme Research Project; Linnaeus Center through the Swedish Research Council (Vetenskapsradet)

Vid tiden för disputation förelåg publikationen som manuskript

Available from: 2014-05-23 Created: 2014-05-23 Last updated: 2017-12-05
2. Indoor Positioning Using Ultrawideband and Inertial Measurements
Open this publication in new window or tab >>Indoor Positioning Using Ultrawideband and Inertial Measurements
2015 (English)In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 64, no 4, 1293-1303 p.Article in journal (Refereed) Published
Abstract [en]

In this paper, we present an approach to combine measurements from inertial sensors (accelerometers and gyroscopes) with time-of-arrival measurements from an ultrawideband (UWB) system for indoor positioning. Our algorithm uses a tightly coupled sensor fusion approach, where we formulate the problem as a maximum a posteriori (MAP) problem that is solved using an optimization approach. It is shown to lead to accurate 6-D position and orientation estimates when compared to reference data from an independent optical tracking system. To be able to obtain position information from the UWB measurements, it is imperative that accurate estimates of the UWB receivers positions and their clock offsets are available. Hence, we also present an easy-to-use algorithm to calibrate the UWB system using a maximum-likelihood (ML) formulation. Throughout this work, the UWB measurements are modeled by a tailored heavy-tailed asymmetric distribution to account for measurement outliers. The heavy-tailed asymmetric distribution works well on experimental data, as shown by analyzing the position estimates obtained using the UWB measurements via a novel multilateration approach.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2015
Keyword
Calibration; heavy-tailed noise distribution; inertial sensors; sensor fusion; ultrawideband (UWB)
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:liu:diva-118060 (URN)10.1109/TVT.2015.2396640 (DOI)000353111900004 ()
Note

Funding Agencies|Control, Autonomy, and Decision-making In Complex Systems (CADICS): a Linnaeus Center - Swedish Research Council (VR); BALANCE: a European Commission FP7 Research Project; Swedish Research Council (VR) [621-2013-5524]

Available from: 2015-05-20 Created: 2015-05-20 Last updated: 2017-12-04
3. An optimization-based approach to human body motion capture using inertial sensors
Open this publication in new window or tab >>An optimization-based approach to human body motion capture using inertial sensors
2014 (English)In: Proceedings of the 19th IFAC World Congress, 2014 / [ed] Boje, Edward; Xia, Xiaohua, International Federation of Automatic Control , 2014, 79-85 p.Conference paper, Published paper (Refereed)
Abstract [en]

In inertial human motion capture, a multitude of body segments are equipped with inertial measurement units, consisting of 3D accelerometers, 3D gyroscopes and 3D magnetometers. Relative position and orientation estimates can be obtained using the inertial data together with a biomechanical model. In this work we present an optimization-based solution to magnetometer-free inertial motion capture. It allows for natural inclusion of biomechanical constraints, for handling of nonlinearities and for using all data in obtaining an estimate. As a proof-of-concept we apply our algorithm to a lower body configuration, illustrating that the estimates are drift-free and match the joint angles from an optical reference system.

Place, publisher, year, edition, pages
International Federation of Automatic Control, 2014
Series
World Congress, ISSN 1474-6670 ; World Congress, Volume# 19 | Part# 1
Keyword
Human body motion capture, optimization, maximum a posteriori estimation, inertial sensors, 6D pose estimation.
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-111543 (URN)10.3182/20140824-6-ZA-1003.02252 (DOI)978-3-902823-62-5 (ISBN)
Conference
19th World Congress of the International Federation of Automatic Control (IFAC), Cape Town, South Africa, August 24-29, 2014
Projects
MC ImpulseCADICSBALANCE
Funder
EU, FP7, Seventh Framework Programme, 1933031801Swedish Research Council, 1933011102
Available from: 2014-10-22 Created: 2014-10-22 Last updated: 2016-12-15Bibliographically approved
4. MEMS-based inertial navigation based on a magnetic field map
Open this publication in new window or tab >>MEMS-based inertial navigation based on a magnetic field map
2013 (English)In: Proceedings of the 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2013, 6466-6470 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents an approach for 6D pose estimation where MEMS inertial measurements are complemented with magnetometer measurements assuming that a model (map) of the magnetic field is known. The resulting estimation problem is solved using a Rao-Blackwellized particle filter. In our experimental study the magnetic field is generated by a magnetic coil giving rise to a magnetic field that we can model using analytical expressions. The experimental results show that accurate position estimates can be obtained in the vicinity of the coil, where the magnetic field is strong.

Keyword
Magnetic field, inertial navigation, state estimation, Rao-Blackwellized particle filter, magnetometer
National Category
Control Engineering Signal Processing
Identifiers
urn:nbn:se:liu:diva-102632 (URN)10.1109/ICASSP.2013.6638911 (DOI)000329611506126 ()
Conference
The 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Vancouver, Canada, May 26-31, 2013
Funder
EU, FP7, Seventh Framework Programme, 1933031801Swedish Research Council, 1933011102
Available from: 2013-12-17 Created: 2013-12-17 Last updated: 2016-12-15

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