scholarly journals Processing Chain for Localization of Magnetoelectric Sensors in Real Time

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5675
Author(s):  
Christin Bald ◽  
Gerhard Schmidt
Keyword(s):  
Magnetic Field ◽  
Real Time ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Source Distribution ◽  
Magnetic Field Sensors ◽  
Processing Chain ◽  
Magnetoelectric Sensors ◽  
Exact Position ◽  
Localization Approach

The knowledge of the exact position and orientation of a sensor with respect to a source (distribution) is essential for the correct solution of inverse problems. Especially when measuring with magnetic field sensors, the positions and orientations of the sensors are not always fixed during measurements. In this study, we present a processing chain for the localization of magnetic field sensors in real time. This includes preprocessing steps, such as equalizing and matched filtering, an iterative localization approach, and postprocessing steps for smoothing the localization outcomes over time. We show the efficiency of this localization pipeline using an exchange bias magnetoelectric sensor. For the proof of principle, the potential of the proposed algorithm performing the localization in the two-dimensional space is investigated. Nevertheless, the algorithm can be easily extended to the three-dimensional space. Using the proposed pipeline, we achieve average localization errors between 1.12 cm and 6.90 cm in a localization area of size 50cm×50cm.

Three-dimensional path planning for unmanned aerial vehicle based on linear programming

Robotica ◽  
2011 ◽  
Vol 30 (5) ◽  
pp. 773-781 ◽  
Author(s):  
Yang Chen ◽  
Jianda Han ◽  
Xingang Zhao
Keyword(s):  
Linear Programming ◽  
Path Planning ◽  
Real Time ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Linear Constraints ◽  
Flying Height ◽  
Ant Colony Optimization Algorithm ◽  
Optimal Velocity ◽  
Aerial Vehicle

SUMMARYIn this paper, an approach based on linear programming (LP) is proposed for path planning in three-dimensional space, in which an aerial vehicle is requested to pursue a target while avoiding static or dynamic obstacles. This problem is very meaningful for many aerial robots, such as unmanned aerial vehicles. First, the tasks of target-pursuit and obstacle-avoidance are modelled with linear constraints in relative coordination according to LP formulation. Then, two weighted cost functions, representing the optimal velocity resolution, are integrated into the final objective function. This resolution, defined to achieve the optimal velocity, deals with the optimization of a pair of orthogonal vectors. Some constraints, such as boundaries of the vehicle velocity, acceleration, sensor range, and flying height, are considered in this method. A number of simulations, under static and dynamic environments, are carried out to validate the performance of generating optimal trajectory in real time. Compared with ant colony optimization algorithm and genetic algorithm, our method has less parameters to tune and can achieve better performance in real-time application.

Three-dimensional magnetic-field sensors

1988 ◽  
Vol 35 (6) ◽  
pp. 771-779 ◽  
Author(s):  
S. Kordic ◽  
P.J.A. Munter
Keyword(s):  
Magnetic Field ◽  
Three Dimensional ◽  
Magnetic Field Sensors

Convolutional Neural Networks for Real-Time Eye Tracking in Interactive Applications

2021 ◽  
pp. 455-473
Author(s):  
Michael Burch ◽  
Andrei Jalba ◽  
Carl van Dueren den Hollander
Keyword(s):  
Eye Tracking ◽  
Real Time ◽  
Network Architecture ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Face Alignment ◽  
Interactive Applications ◽  
Processing Power ◽  
Real Time Applications ◽  
Pose Alignment

Face alignment and eye tracking for interactive applications should be performed with very low latency or users will notice the delay. In this chapter, a face alignment method for real-time applications is introduced featuring a convolutional neural network architecture for face and pose alignment. The performance of the novel method is compared to a face alignment algorithm included in the freely available OpenFace toolkit, which also focuses on real-time applications. The approach exceeds OpenFace's performance on both our own and the 300W test sets in terms of accuracy and robustness but requires significant parallel processing power, currently provided by the GPU. For the eye tracking application, stereo cameras are used as input to determine the position of a user's eyes in three-dimensional space. It does not require synchronized recordings, which may contain redundant information, and instead prefers staggered recordings, which maximize the number of possible model updates.

Real time three-dimensional space video rate sensors for millimeter waves imaging based very inexpensive plasma LED lamps

2014 ◽  
Author(s):  
Assaf Levanon ◽  
Yitzhak Yitzhaky ◽  
Natan S. Kopeika ◽  
Daniel Rozban ◽  
Amir Abramovich
Keyword(s):  
Real Time ◽  
Millimeter Waves ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Three Dimensional Space

Dipole Positioning Recognition Using Neural Networks

2014 ◽  
Vol 605 ◽  
pp. 673-676
Author(s):  
Katerina Skouta
Keyword(s):  
Magnetic Field ◽  
Neural Networks ◽  
Magnetic Sensors ◽  
Sufficient Information ◽  
Naval Vessel ◽  
Magnetic Field Sensors ◽  
Single Dipole ◽  
Exact Position ◽  
Magnetic Mass ◽  
Measured Magnetic Field

A ships position could be detected by its magnetic signature. A crucial issue, regarding this approach for naval vessel monitoring, is the difficulty in defining the appropriate number of magnetic sensors needed and their respective configuration, in order to predict accurately the position of the magnetic mass through the measured magnetic field intensities on a specific boundary. In the present paper, this problem is dealt downscaled at tracing the exact position and orientation of a single dipole. In particular, Neural Networks, properly calibrated, are implemented as a method for the detection of the position and the orientation of a dipole through the measured magnetic field inducted. The results indicate that measurements of two magnetic field sensors at the boundary could provide sufficient information about the dipoles position, with a certainty of 99%.

scholarly journals Estimation of Magnetic Field Growth and Construction of Adaptive Mesh in Corner Domain for the Magnetostatic Problem in Three-Dimensional Space

2018 ◽  
Vol 173 ◽  
pp. 03019
Author(s):  
Eugene Perepelkin ◽  
Aleksandr Tarelkin
Keyword(s):  
Magnetic Field ◽  
Smooth Boundary ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Adaptive Mesh ◽  
Field Growth ◽  
Magnetostatic Problem ◽  
Research Facilities ◽  
The Magnetic Field ◽  
Three Dimensional Space

A magnetostatics problem arises when searching for the distribution of the magnetic field generated by magnet systems of many physics research facilities, e.g., accelerators. The domain in which the boundary-value problem is solved often has a piecewise smooth boundary. In this case, numerical calculations of the problem require consideration of the solution behavior in the corner domain. In this work we obtained an upper estimation of the magnetic field growth using integral formulation of the magnetostatic problem and propose a method for condensing the differential mesh near the corner domain of the vacuum in the three-dimensional space based on this estimation.

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