Attitude Estimation of Underwater Vehicles Using Field Measurements and Bias Compensation.
ABSTRACT: This paper proposes a method of estimating the attitude of an underwater vehicle. The proposed method uses two field measurements, namely, a gravitational field and a magnetic field represented in terms of vectors in three-dimensional space. In many existing methods that convert the measured field vectors into Euler angles, the yaw accuracy is affected by the uncertainty of the gravitational measurement and by the uncertainty of the magnetic field measurement. Additionally, previous methods have used the magnetic field measurement under the assumption that the magnetic field has only a horizontal component. The proposed method utilizes all field measurement components as they are, without converting them into Euler angles. The bias in the measured magnetic field vector is estimated and compensated to take full advantage of all measured field vector components. Because the proposed method deals with the measured field independently, uncertainties in the measured vectors affect the attitude estimation separately without adding up. The proposed method was tested by conducting navigation experiments with an unmanned underwater vehicle inside test tanks. The results were compared with those obtained by other methods, wherein the Euler angles converted from the measured field vectors were used as measurements.
Project description:The calibration problem of binocular stereo vision rig is critical for its practical application. However, most existing calibration methods are based on manual off-line algorithms for specific reference targets or patterns. In this paper, we propose a novel simultaneous localization and mapping (SLAM)-based self-calibration method designed to achieve real-time, automatic and accurate calibration of the binocular stereo vision (BSV) rig's extrinsic parameters in a short period without auxiliary equipment and special calibration markers, assuming the intrinsic parameters of the left and right cameras are known in advance. The main contribution of this paper is to use the SLAM algorithm as our main tool for the calibration method. The method mainly consists of two parts: SLAM-based construction of 3D scene point map and extrinsic parameter calibration. In the first part, the SLAM mainly constructs a 3D feature point map of the natural environment, which is used as a calibration area map. To improve the efficiency of calibration, a lightweight, real-time visual SLAM is built. In the second part, extrinsic parameters are calibrated through the 3D scene point map created by the SLAM. Ultimately, field experiments are performed to evaluate the feasibility, repeatability, and efficiency of our self-calibration method. The experimental data shows that the average absolute error of the Euler angles and translation vectors obtained by our method relative to the reference values obtained by Zhang's calibration method does not exceed 0.5? and 2 mm, respectively. The distribution range of the most widely spread parameter in Euler angles is less than 0.2? while that in translation vectors does not exceed 2.15 mm. Under the general texture scene and the normal driving speed of the mobile robot, the calibration time can be generally maintained within 10 s. The above results prove that our proposed method is reliable and has practical value.
Project description:An accurate motion model and reliable measurements are required for autonomous underwater vehicle localization and navigation in underwater environments. However, without a propeller, underwater gliders have limited maneuverability and carrying capacity, which brings difficulties for modeling and measuring. In this paper, an extended Kalman filter (EKF)-based method, combining a modified kinematic model of underwater gliders with the travel-time differences between signals received from a single beacon, is proposed for estimating the glider positions in a predict-update cycle. First, to accurately establish a motion model for underwater gliders moving in the ocean, we introduce two modification parameters, the attack and drift angles, into a kinematic model of underwater gliders, along with depth-averaged current velocities. The attack and drift angles are calculated based on the coefficients of hydrodynamic forces and the sensor-measured angle variation over time. Then, instead of satisfying synchronization requirements, the travel-time differences between signals received from a single beacon, multiplied by the sound speed, are taken as the measurements. To further reduce the EKF estimation error, the Rauch-Tung-Striebel (RTS) smoothing method is merged into the EKF system. The proposed method is tested in a virtual spatiotemporal environment from an ocean model. The experimental results show that the performance of the RTS-EKF estimate is improved when compared with the motion model estimate, especially by 46% at the inflection point, at least in the particular study developed in this article.
Project description:Gravity aided inertial navigation system (GAINS), which uses earth gravitational anomaly field for navigation, holds strong potential as an underwater navigation system. The gravity matching algorithm is one of the key factors in GAINS. Existing matching algorithms cannot guarantee the matching accuracy in the matching algorithms based gravity aided navigation when the initial errors are large. Evolutionary algorithms, which are mostly have the ability of global optimality and fast convergence, can be used to solve the gravity matching problem under large initial errors. However, simply applying evolutionary algorithms to GAINS may lead to false matching. Therefore, in order to deal with the underwater gravity matching problem, it is necessary to improve the traditional evolutionary algorithms. In this paper, an affine transformation based artificial bee colony (ABC) algorithm, which can greatly improve the positioning precision under large initial errors condition, is developed. The proposed algorithm introduces affine transformation to both initialization process and evolutionary process of ABC algorithm. The single-point matching strategy is replaced by the strategy of matching a sequence of several consecutive position vectors. In addition, several constraints are introduced to the process of evolution by using the output characteristics of the inertial navigation system (INS). Simulations based on the actual gravity anomaly base map have been performed for the validation of the proposed algorithm.
Project description:Using diamagnetic levitation, we have exposed A. thaliana in vitro callus cultures to five environments with different levels of effective gravity (from levitation i.e. simulated mg* to 2g*) and magnetic fields (10.1 to 16.5 Tesla) and we have compared the results with those of similar experiments done in a Random Position Machine (simulated micro g) and a Large Diameter Centrifuge (2g) free of high magnetic fields. Microarray analysis indicates that there are changes in overall gene expression of the cultured cells exposed to these unusual environments but also that gravitational and magnetic field produce synergic variations in the steady state of the transcriptional profile of A. thaliana. Significant changes in the expression of structural, abiotic stress and secondary metabolism genes were observed into the magnet field. These results confirm that the strong magnetic field, both at micro g* or 2g*, has a significant effect on the expression of these genes but subtle gravitational effects are still observable. These subtle responses to microgravity environments are opposite to the ones observed in a hypergravity one. Overall design: seven-condition experiment, MM2D Arabidopsis culture callus control vs. Treatment (altered gravity simulation, GBF). Three GBF were used (LDC (2g) + control, RPM (mg) + control and Magnet (mg*, 0.1g*, 1g*, 1.9g*, 2g*) + control). Biological replicates: 3 replicates in all conditions and controls except 1.9g* (2 replicates)
Project description:Computationally efficient 3D orientation (3DO) tracking using gyroscope angular velocity measurements enables a short execution time and low energy consumption for the computing device. These are essential requirements in today's wearable device environments, which are characterized by limited resources and demands for high energy autonomy. We show that the computational efficiency of 3DO tracking is significantly improved by correctly interpreting each triplet of gyroscope measurements as simultaneous (using the rotation vector called the Simultaneous Orthogonal Rotation Angle, or SORA) rather than as sequential (using Euler angles) rotation. For an example rotation of 90°, depending on the change in the rotation axis, using Euler angles requires 35 to 78 times more measurement steps for comparable levels of accuracy, implying a higher sampling frequency and computational complexity. In general, the higher the demanded 3DO accuracy, the higher the computational advantage of using the SORA. Furthermore, we demonstrate that 12 to 14 times faster execution is achieved by adapting the SORA-based 3DO tracking to the architecture of the executing low-power ARM Cortex® M0+ microcontroller using only integer arithmetic, lookup tables, and the small-angle approximation. Finally, we show that the computational efficiency is further improved by choosing the appropriate 3DO computational method. Using rotation matrices is 1.85 times faster than using rotation quaternions when 3DO calculations are performed for each measurement step. On the other hand, using rotation quaternions is 1.75 times faster when only the final 3DO result of several consecutive rotations is needed. We conclude that by adopting the presented practices, the clock frequency of a processor computing the 3DO can be significantly reduced. This substantially prolongs the energy autonomy of the device and enhances its usability in day-to-day measurement scenarios.
Project description:A recommended field method to assess body composition in adolescent sprint athletes is currently lacking. Existing methods developed for non-athletic adolescents were not longitudinally validated and do not take maturation status into account. This longitudinal study compared two field methods, i.e., a Bio Impedance Analysis (BIA) and a skinfold based equation, with underwater densitometry to track body fat percentage relative to years from age at peak height velocity in adolescent sprint athletes. In this study, adolescent sprint athletes (34 girls, 35 boys) were measured every 6 months during 3 years (age at start = 14.8 ± 1.5 yrs in girls and 14.7 ± 1.9 yrs in boys). Body fat percentage was estimated in 3 different ways: 1) using BIA with the TANITA TBF 410; 2) using a skinfold based equation; 3) using underwater densitometry which was considered as the reference method. Height for age since birth was used to estimate age at peak height velocity. Cross-sectional analyses were performed using repeated measures ANOVA and Pearson correlations between measurement methods at each occasion. Data were analyzed longitudinally using a multilevel cross-classified model with the PROC Mixed procedure. In boys, compared to underwater densitometry, the skinfold based formula revealed comparable values for body fatness during the study period whereas BIA showed a different pattern leading to an overestimation of body fatness starting from 4 years after age at peak height velocity. In girls, both the skinfold based formula and BIA overestimated body fatness across the whole range of years from peak height velocity. The skinfold based method appears to give an acceptable estimation of body composition during growth as compared to underwater densitometry in male adolescent sprinters. In girls, caution is warranted when interpreting estimations of body fatness by both BIA and a skinfold based formula since both methods tend to give an overestimation.
Project description:Self-sustaining numerical dynamos are used to infer the sources of low-frequency secular variation of the geomagnetic field. Gravitational dynamo models powered by compositional convection in an electrically conducting, rotating fluid shell exhibit several regimes of magnetic field behavior with an increasing Rayleigh number of the convection, including nearly steady dipoles, chaotic nonreversing dipoles, and chaotic reversing dipoles. The time average dipole strength and dipolarity of the magnetic field decrease, whereas the dipole variability, average dipole tilt angle, and frequency of polarity reversals increase with Rayleigh number. Chaotic gravitational dynamos have large-amplitude dipole secular variation with maximum power at frequencies corresponding to a few cycles per million years on Earth. Their external magnetic field structure, dipole statistics, low-frequency power spectra, and polarity reversal frequency are comparable to the geomagnetic field. The magnetic variability is driven by the Lorentz force and is characterized by an inverse correlation between dynamo magnetic and kinetic energy fluctuations. A constant energy dissipation theory accounts for this inverse energy correlation, which is shown to produce conditions favorable for dipole drift, polarity reversals, and excursions.
Project description:Current-induced magnetic domain wall (DW) motion is an important operating principle of spintronic devices. Injected current generates spin torques (STs) on the DWs in two ways. One is the spin transfer from magnetic domains to the walls by the current flowing in the magnet. Current flow in attached heavy metals also generates another ST because of the spin-Hall effect. Both phenomena explain the wall motions well; therefore, their respective contribution is an important issue. Here, we show the simultaneous measurement of both torques by using magnetic facet domains that form mountain-shaped domains with straight walls. When the STs and the external magnetic field push the walls in opposite directions, the walls should have equilibrium angles to create balanced states. Such angles can be modulated by an additional in-plane magnetic field. Angle measurements distinguish the STs because each torque has a distinct mechanism related to the DW structure.
Project description:Using diamagnetic levitation, we have exposed A. thaliana in vitro callus cultures to five environments with different levels of effective gravity (from levitation i.e. simulated mg* to 2g*) and magnetic fields (10.1 to 16.5 Tesla) and we have compared the results with those of similar experiments done in a Random Position Machine (simulated micro g) and a Large Diameter Centrifuge (2g) free of high magnetic fields. Microarray analysis indicates that there are changes in overall gene expression of the cultured cells exposed to these unusual environments but also that gravitational and magnetic field produce synergic variations in the steady state of the transcriptional profile of A. thaliana. Significant changes in the expression of structural, abiotic stress and secondary metabolism genes were observed into the magnet field. These results confirm that the strong magnetic field, both at micro g* or 2g*, has a significant effect on the expression of these genes but subtle gravitational effects are still observable. These subtle responses to microgravity environments are opposite to the ones observed in a hypergravity one. seven-condition experiment, MM2D Arabidopsis culture callus control vs. Treatment (altered gravity simulation, GBF). Three GBF were used (LDC (2g) + control, RPM (mg) + control and Magnet (mg*, 0.1g*, 1g*, 1.9g*, 2g*) + control). Biological replicates: 3 replicates in all conditions and controls except 1.9g* (2 replicates)
Project description:Biological macromolecules can adopt multiple conformational and compositional states due to structural flexibility and alternative subunit assemblies. This structural heterogeneity poses a major challenge in the study of macromolecular structure using single-particle electron microscopy. We propose a fully automated, unsupervised method for the three-dimensional reconstruction of multiple structural models from heterogeneous data. As a starting reference, our method employs an initial structure that does not account for any heterogeneity. Then, a multi-stage clustering is used to create multiple models representative of the heterogeneity within the sample. The multi-stage clustering combines an existing approach based on Multivariate Statistical Analysis to perform clustering within individual Euler angles, and a newly developed approach to sort out class averages from individual Euler angles into homogeneous groups. Structural models are computed from individual clusters. The whole data classification is further refined using an iterative multi-model projection-matching approach. We tested our method on one synthetic and three distinct experimental datasets. The tests include the cases where a macromolecular complex exhibits structural flexibility and cases where a molecule is found in ligand-bound and unbound states. We propose the use of our approach as an efficient way to reconstruct distinct multiple models from heterogeneous data.