| 1. |
- Isaksson, Alf, et al.
(författare)
-
Using horizon estimation and nonlinear optimization for grey-box identification
- 2015
-
Ingår i: Journal of Process Control. - : Elsevier. - 0959-1524 .- 1873-2771. ; 30, s. 69-79
-
Tidskriftsartikel (refereegranskat)abstract
- An established method for grey-box identification is to use maximum-likelihood estimation for the nonlinear case implemented via extended Kalman filtering. In applications of (nonlinear) model predictive control a more and more common approach for the state estimation is to use moving horizon estimation, which employs (nonlinear) optimization directly on a model for a whole batch of data. This paper shows that, in the linear case, horizon estimation may also be used for joint parameter estimation and state estimation, as long as a bias correction based on the Kalman filter is included. For the nonlinear case two special cases are presented where the bias correction can be determined without approximation. A procedure how to approximate the bias correction for general nonlinear systems is also outlined. (C) 2015 Elsevier Ltd. All rights reserved.
|
|
| 2. |
- Kok, Manon, et al.
(författare)
-
A Fast and Robust Algorithm for Orientation Estimation Using Inertial Sensors
- 2019
-
Ingår i: IEEE Signal Processing Letters. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1070-9908 .- 1558-2361. ; 26:11, s. 1673-1677
-
Tidskriftsartikel (refereegranskat)abstract
- We present a novel algorithm for online, real-time orientation estimation. Our algorithm integrates gyroscope data and corrects the resulting orientation estimate for integration drift using accelerometer and magnetometer data. This correction is computed, at each time instance, using a single gradient descent step with fixed step length. This fixed step length results in robustness against model errors, e.g., caused by large accelerations or by short-term magnetic field disturbances, which we numerically illustrate using Monte Carlo simulations. Our algorithm estimates a three-dimensional update to the orientation rather than the entire orientation itself. This reduces the computational complexity by approximately 1/3 with respect to the state of the art. It also improves the quality of the resulting estimates, specifically when the orientation corrections are large. We illustrate the efficacy of the algorithm using experimental data.
|
|
| 3. |
- Kok, Manon, 1982-, et al.
(författare)
-
A Scalable and Distributed Solution to the Inertial Motion Capture Problem
- 2016
-
Ingår i: Proceedings of the 19th International Conference on Information Fusion. - : Institute of Electrical and Electronics Engineers (IEEE). - 9780996452748 ; , s. 1348-1355
-
Konferensbidrag (refereegranskat)abstract
- In inertial motion capture, a multitude of body segments are equipped with inertial sensors, consisting of 3D accelerometers and 3D gyroscopes. Using an optimization-based approach to solve the motion capture problem allows for natural inclusion of biomechanical constraints and for modeling the connection of the body segments at the joint locations. The computational complexity of solving this problem grows both with the length of the data set and with the number of sensors and body segments considered. In this work, we present a scalable and distributed solution to this problem using tailored message passing, capable of exploiting the structure that is inherent in the problem. As a proof-of-concept we apply our algorithm to data from a lower body configuration.
|
|
| 4. |
|
|
| 5. |
- Kok, Manon, 1982-, et al.
(författare)
-
An optimization-based approach to human body motion capture using inertial sensors
- 2014
-
Ingår i: Proceedings of the 19th IFAC World Congress, 2014. - : International Federation of Automatic Control. - 9783902823625 ; , s. 79-85
-
Konferensbidrag (refereegranskat)abstract
- 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.
|
|
| 6. |
- Kok, Manon, 1982-, et al.
(författare)
-
Calibration of a magnetometer in combination with inertial sensors
- 2012
-
Ingår i: Proceedings of the 15th International Conference on Information Fusion (FUSION). - : IEEE conference proceedings. - 9780982443842 ; , s. 787-793
-
Konferensbidrag (refereegranskat)abstract
- Measurements from magnetometers and inertial sensors (accelerometers and gyroscopes) can be combined to give 3D orientation estimates. In order to obtain accurate orientation estimates it is imperative that the magnetometer and inertial sensor axes are aligned and that the magnetometer is properly calibrated for both sensor errors as well as presence of magnetic distortions. In this work we derive an easy-to-use calibration algorithm that can be used to calibrate a combination of a magnetometer and inertial sensors. The algorithm compensates for any static magnetic distortions created by the sensor plat- form, magnetometer sensor errors and determines the alignment between the magnetometer and the inertial sensor axes. The resulting calibration procedure does not require any additional hardware. We make use of probabilistic models and obtain the calibration algorithm as the solution to a maximum likelihood problem. The efficacy of the proposed algorithm is illustrated using experimental data collected from a sensor unit placed in a magnetically disturbed environment onboard a jet aircraft.
|
|
| 7. |
- Kok, Manon, et al.
(författare)
-
Indoor Positioning Using Ultrawideband and Inertial Measurements
- 2015
-
Ingår i: IEEE Transactions on Vehicular Technology. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9545 .- 1939-9359. ; 64:4, s. 1293-1303
-
Tidskriftsartikel (refereegranskat)abstract
- 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.
|
|
| 8. |
- Kok, Manon, et al.
(författare)
-
Magnetometer calibration using inertial sensors
- 2016
-
Ingår i: IEEE Sensors Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 1530-437X .- 1558-1748. ; 16:14, s. 5679-5689
-
Tidskriftsartikel (refereegranskat)abstract
- 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.
|
|
| 9. |
- Kok, Manon, 1982-, et al.
(författare)
-
Maximum likelihood calibration of a magnetometer using inertial sensors
- 2014
-
Ingår i: Proceedings of the 19th IFAC World Congress, 2014. - : International Federation of Automatic Control. - 9783902823625 ; , s. 92-97
-
Konferensbidrag (refereegranskat)abstract
- Magnetometers and inertial sensors (accelerometers and gyroscopes) are widely used to estimate 3D orientation. For the orientation estimates to be accurate, the sensor axes need to be aligned and the magnetometer needs to be calibrated for sensor errors and for the presence of magnetic disturbances. In this work we use a grey-box system identification approach to compute maximum likelihood estimates of the calibration parameters. An experiment where the magnetometer data is highly disturbed shows that the algorithm works well on real data, providing good calibration results and improved heading estimates. We also provide an identifiability analysis to understand how much rotation is needed to be able to solve the calibration problem.
|
|
| 10. |
- Kok, Manon, 1982-, et al.
(författare)
-
MEMS-based inertial navigation based on a magnetic field map
- 2013
-
Ingår i: Proceedings of t<em>he 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP)</em>. ; , s. 6466-6470
-
Konferensbidrag (refereegranskat)abstract
- 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.
|
|
