scholarly journals New Approaches to the Integration of Navigation Systems for Autonomous Unmanned Vehicles (UAV)

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3010 ◽  
Author(s):  
Ivan Konovalenko ◽  
Elena Kuznetsova ◽  
Alexander Miller ◽  
Boris Miller ◽  
Alexey Popov ◽  
...  
Keyword(s):  
Projective Transformation ◽  
Unmanned Vehicles ◽  
Position Estimation ◽  
Parameters Estimation ◽  
Video Data ◽  
Navigation Systems ◽  
Aspect Angle ◽  
Work Related ◽  
New Approaches ◽  
Angular Velocities

The article presents an overview of the theoretical and experimental work related to unmanned aerial vehicles (UAVs) motion parameters estimation based on the integration of video measurements obtained by the on-board optoelectronic camera and data from the UAV’s own inertial navigation system (INS). The use of various approaches described in the literature which show good characteristics in computer simulations or in fairly simple conditions close to laboratory ones demonstrates the sufficient complexity of the problems associated with adaption of camera parameters to the changing conditions of a real flight. In our experiments, we used computer simulation methods applying them to the real images and processing methods of videos obtained during real flights. For example, it was noted that the use of images that are very different in scale and in the aspect angle from the observed images in flight makes it very difficult to use the methodology of singular points. At the same time, the matching of the observed and reference images using rectilinear segments, such as images of road sections and the walls of the buildings look quite promising. In addition, in our experiments we used the projective transformation matrix computation from frame to frame, which together with the filtering estimates for the coordinate and angular velocities provides additional possibilities for estimating the UAV position. Data on the UAV position determining based on the methods of video navigation obtained during real flights are presented. New approaches to video navigation obtained using the methods of conjugation rectilinear segments, characteristic curvilinear elements and segmentation of textured and colored regions are demonstrated. Also the application of the method of calculating projective transformations from frame-to-frame is shown which gives estimates of the displacements and rotations of the apparatus and thereby serves to the UAV position estimation by filtering. Thus, the aim of the work was to analyze various approaches to UAV navigation using video data as an additional source of information about the position and velocity of the vehicle.

Design, modeling, and simulation of an INS system using an asymmetric structure of six accelerometers and its error analysis in the ECEF frame

2016 ◽  
Vol 231 (13) ◽  
pp. 2345-2361 ◽  
Author(s):  
Vahid Ghasemzadeh ◽  
Mohammad M Arefi
Keyword(s):  
Error Analysis ◽  
Lower Cost ◽  
Inertial Navigation ◽  
Asymmetric Structure ◽  
Navigation Systems ◽  
Inertial Navigation Systems ◽  
Symmetric Structure ◽  
Angular Velocities ◽  
Dynamic Relations ◽  
Short Time

The inertial navigation system is one of the most important and common methods of navigation. In this system, accelerometers and gyroscopes are used to measure linear accelerations and angular velocities, respectively. Accelerometers have simpler manufacture techniques, lower cost, and smaller volume and weight in comparison with gyroscopes. Therefore, in some application of navigation systems, non-gyro inertial navigation systems based on accelerometers are used. In this paper, an asymmetric structure of six accelerometers is proposed. Then dynamic relations of this structure are extracted. This structure and its relations can determine linear accelerations and angular velocities, completely. Moreover, the algorithm of inertial navigation in earth centered earth fixed (ECEF) frame is suggested. Error analysis as of the most important issues in inertial navigation is discussed. Thus, bias, misalignment, sensitivity, and noise of accelerometers are modeled appropriately. In addition, a symmetric structure of accelerometers is proposed and its equations are derived. Finally, the designed system, error model of accelerometers, and algorithm of inertial navigation in ECEF frame are simulated. The results of simulation show that the designed system has suitable accuracy and applications for short time navigation. Furthermore, results confirm that the proposed asymmetric structure requires less accelerometer in comparison with symmetric structure.

Adaptive estimation of UVs navigation parameters by irregular inertial-satellite measurements

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sergey V. Sokolov ◽  
Arthur I. Novikov
Keyword(s):  
Kalman Filter ◽  
Adaptive Estimation ◽  
Unmanned Vehicles ◽  
Dispersion Matrix ◽  
Navigation Systems ◽  
Satellite Measurements ◽  
Preliminary Calculation ◽  
Adaptation Algorithm ◽  
Estimation Errors ◽  
Content Type

PurposeThere are shortcomings of modern methods of ensuring the stability of Kalman filtration in unmanned vehicles’ (UVs) navigation systems under the condition of a priori uncertainty of the dispersion matrix of measurement interference. First, it is the absence of strict criteria for the selection of adaptation coefficients in the calculation of the a posteriori covariance matrix. Secondly, it is the impossibility of adaptive estimation in real time from the condition of minimum covariance of the updating sequence due to the necessity of its preliminary calculation.Design/methodology/approachThis paper considers a new approach to the construction of the Kalman filter adaptation algorithm. The algorithm implements the possibility of obtaining an accurate adaptive estimation of navigation parameters for integrated UVs inertial-satellite navigation systems, using the correction of non-periodic and unstable inertial estimates by high-precision satellite measurements. The problem of adaptive estimation of the noise dispersion matrix of the meter in the Kalman filter can be solved analytically using matrix methods of linear algebra. A numerical example illustrates the effectiveness of the procedure for estimating the state vector of the UVs’ navigation systems.FindingsAdaptive estimation errors are sharply reduced in comparison with the traditional scheme to the range from 2 to 7 m in latitude and from 1.5 to 4 m in longitude.Originality/valueThe simplicity and accuracy of the proposed algorithm provide the possibility of its effective application to the widest class of UVs’ navigation systems.

Position and Velocity Navigation Systems for Unmanned Vehicles

2009 ◽  
Vol 17 (3) ◽  
pp. 707-715 ◽  
Author(s):  
P. Batista ◽  
C. Silvestre ◽  
P. Oliveira
Keyword(s):  
Unmanned Vehicles ◽  
Navigation Systems

INERTIA PARAMETERS ESTIMATION OF PLANAR OBJECT ON ROBOT PUSHING OPERATION

2009 ◽  
Vol 06 (04) ◽  
pp. 239-247 ◽  
Author(s):  
YONG YU ◽  
TETSU ARIMA ◽  
SHOWZOW TSUJIO
Keyword(s):  
Experimental Verification ◽  
Center Of Mass ◽  
Point Contact ◽  
Parameters Estimation ◽  
Moment Of Inertia ◽  
Inertia Parameters ◽  
Angular Velocities ◽  
Unknown Object

This paper proposes a technique that can estimate the inertia parameters of a graspless unknown object, which is pushed by robot fingers. Using the fingertip different accelerations (or angular accelerations), velocities (or angular velocities) and forces information measured in pushing operations, the algorithms to estimate the object mass (or moment of inertia) are described. Then, a line called C.M. Line, is defined in this paper. The line contains the center of mass and is between two fingertips which are in point-contact with an object side. By using two or more orientation-different C.M. lines, an algorithm to estimate the center of mass of the object is given. Lastly, experimental verification on the proposed approach is performed and its results are outlined.

scholarly journals VIMO: A Visual-Inertial-Magnetic Navigation System Based on Non-Linear Optimization

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4386
Author(s):  
Jingzhe Wang ◽  
Leilei Li ◽  
Huan Yu ◽  
Xunya Gui ◽  
Zucheng Li
Keyword(s):  
Large Scale ◽  
Linear Optimization ◽  
Position Estimation ◽  
Measurement Unit ◽  
Navigation Systems ◽  
Non Linear ◽  
Outdoor Environments ◽  
Novel Method ◽  
And Performance ◽  
Inertial Measurements

Visual-inertial navigation systems are credited with superiority over both pure visual approaches and filtering ones. In spite of the high precision many state-of-the-art schemes have attained, yaw remains unobservable in those systems all the same. More accurate yaw estimation not only means more accurate attitude calculation but also leads to better position estimation. This paper presents a novel scheme that combines visual and inertial measurements as well as magnetic information for suppressing deviation in yaw. A novel method for initializing visual-inertial-magnetic odometers, which recovers the directions of magnetic north and gravity, the visual scalar factor, inertial measurement unit (IMU) biases etc., has been conceived, implemented, and validated. Based on non-linear optimization, a magnetometer cost function is incorporated into the overall optimization objective function as a yawing constraint among others. We have done extensive research and collected several datasets recorded in large-scale outdoor environments to certify the proposed system’s viability, robustness, and performance. Cogent experiments and quantitative comparisons corroborate the merits of the proposed scheme and the desired effect of the involvement of magnetic information on the overall performance.

scholarly journals Accuracy in WiFi Access Point Position Estimation Using Round Trip Time

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3828
Author(s):  
Miquel Garcia-Fernandez ◽  
Isaac Hoyas-Ester ◽  
Alex Lopez-Cruces ◽  
Malgorzata Siutkowska ◽  
Xavier Banqué-Casanovas
Keyword(s):  
Access Point ◽  
Position Estimation ◽  
Global Navigation Satellite Systems ◽  
Automated System ◽  
Navigation Systems ◽  
Round Trip Time ◽  
Round Trip ◽  
Access Points ◽  
Trip Time ◽  
Hardware Biases

WiFi Round Trip Time (RTT) unlocks meter level accuracies in user terminal positions where no other navigation systems, such as Global Navigation Satellite Systems (GNSS), are able to (e.g., indoors). However, little has been done so far to obtain a scalable and automated system that computes the position of the WiFi Access Points (WAP) using RTT and that is able to estimate, in addition to the position, the hardware biases that offset the WiFi ranging measurements. These biases have a direct impact on the ultimate position accuracy of the terminals. This work proposes a method in which the computation of the WiFi Access Points positions and hardware biases (i.e., products) can be estimated based on the ranges and position fixes provided by user terminals (i.e., inverse positioning) and details how this can be improved if raw GNSS measurements (pseudoranges and carrier phase) are also available in the terminal. The data setup used to obtain a performance assessment was configured in a benign scenario (open sky with no obstructions) in order to obtain an upper boundary on the positioning error that can be achieved with the proposed method. Under these conditions, accuracies better than 1.5 m were achieved for the WAP position and hardware bias. The proposed method is suitable to be implemented in an automated manner, without having to rely on dedicated campaigns to survey 802.11mc-compliant WAPs. This paper offers a technique to automatically estimate both mild-indoor WAP products (where terminals have both Wi-Fi RTT and GNSS coverage) and deep-indoor WAP (with no GNSS coverage where the terminals obtain their position exclusively from previously estimated mild-indoor WAPs).

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