scholarly journals Autonomous Navigation System of an Unmanned Aerial Vehicle for Structural Inspection

2021 ◽  
Vol 16 (3) ◽  
pp. 216-222
Author(s):  
Sungwook Jung ◽  
Duckyu Choi ◽  
Seungwon Song ◽  
Hyun Myung
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Navigation System ◽  
Autonomous Navigation ◽  
Aerial Vehicle ◽  
Structural Inspection ◽  
Autonomous Navigation System

An autonomous navigation system integrated with air data and bionic polarization information

2019 ◽  
Vol 41 (13) ◽  
pp. 3679-3687
Author(s):  
Xiaoyu Guo ◽  
Jian Yang ◽  
Tao Du ◽  
Wanquan Liu
Keyword(s):  
Navigation System ◽  
Autonomous Navigation ◽  
Angle Measurement ◽  
Measurement Unit ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Aerial Vehicle ◽  
Polarization Sensor ◽  
Output Information ◽  
Autonomous Navigation System

One of the most significant challenges for an unmanned aerial vehicle (UAV) is to autonomously navigate in complex environments, as the signals from the global positioning system (GPS) are subject to disturbance and interference. To improve the autonomy and availability of the UAV navigation system without GPS, we design a new autonomous navigation system and implement it for real applications in this paper, in which one integrates the inertial measurement unit (IMU), the bionic polarization sensor (BPS), and the air data system (ADS). The BPS can provide effective heading angle measurement, and the ADS is used to output information for continuous velocity and height. The combination of BPS and ADS is a solution the inertial error drift. Kalman filter is selected to estimate the error state of the integrated navigation system based on the measurements from the BPS and ADS, and then the estimation is used to correct the navigation system error in real time. The simulation and experimental results have shown that the new integrated navigation system can perform with high precision and autonomy without GPS signal.

Distributed Filtering-Based Autonomous Navigation System of UAV

2015 ◽  
Vol 03 (01) ◽  
pp. 17-34 ◽  
Author(s):  
Long Zhao ◽  
Ding Wang ◽  
Baoqi Huang ◽  
Lihua Xie
Keyword(s):  
Kalman Filter ◽  
Flight Control ◽  
Navigation System ◽  
Autonomous Navigation ◽  
Vertical Channel ◽  
Positioning System ◽  
Vision Positioning ◽  
Aerial Vehicle ◽  
Sensor Information ◽  
Autonomous Navigation System

In this paper, we propose a systematic framework for the autonomous navigation system based on distributed filtering for an Unmanned Aerial Vehicle (UAV). The proposed framework consists of the design and algorithm of the autonomous navigation. Therein, the camera mounted on the UAV functions as a navigation sensor targeted for navigation and positioning. In order to reduce the computational complexity and exclude the risk caused by Global Positioning System (GPS) outage, an autonomous navigation system based on distributed filtering is designed and realized. When GPS is available by monitoring the GPS integrity, sensor information from Strapdown Inertial Navigation System (SINS) and GPS is fused using a 7-state Conventional Kalman Filter (CKF) to estimate the full UAV state (position, velocity and attitude); when GPS is unavailable, sensor information from gyroscopes, accelerometers and magnetometer is fused using a 4-state Extended Kalman Filter (EKF) to estimate the attitude and heading of the UAV, and sensor information from SINS and vision positioning system is fused using a 7-state Incoordinate Interval Kalman Filter (IIKF) to estimate the position and velocity of the UAV. In addition, the second-order vertical channel damping loop is adopted to fuse measurements from a barometer with those of SINS, which suppresses the divergence of the vertical channel error and makes the altitude information calculated by SINS trustable. Both ground and flight experiments of the autonomous navigation system have been carried out. The test results show that the system can provide stabilized attitude information in long durations, and can realize the automatic flight control of UAV.

Study of the route correction system for the on-board navigation system of an unmanned aerial vehicle on the grounds of radar images of the terrain

2020 ◽  
pp. 129-134
Keyword(s):  
Predictive Model ◽  
Unmanned Aerial Vehicle ◽  
Predictive Models ◽  
Navigation System ◽  
Error Compensation ◽  
Compensation Scheme ◽  
Radar Images ◽  
Aerial Vehicle ◽  
System Errors ◽  
Correction System

The system of route correction of an unmanned aerial vehicle (UAV) is considered. For the route correction the on-board radar complex is used. In conditions of active interference, it is impossible to use radar images for the route correction so it is proposed to use the on-board navigation system with algorithmic correction. An error compensation scheme of the navigation system in the output signal using the algorithm for constructing a predictive model of the system errors is applied. The predictive model is building using the genetic algorithm and the method of group accounting of arguments. The quality comparison of the algorithms for constructing predictive models is carried out using mathematical modeling.

Accuracy improvement in 3D laser scanner based on dynamic triangulation for autonomous navigation system

2017 ◽  
Author(s):  
Oscar Real-Moreno ◽  
Julio C. Rodriguez-Quinonez ◽  
Oleg Sergiyenko ◽  
Luis C. Basaca-Preciado ◽  
Daniel Hernandez-Balbuena ◽  
...  
Keyword(s):  
Navigation System ◽  
Autonomous Navigation ◽  
Laser Scanner ◽  
Accuracy Improvement ◽  
Autonomous Navigation System

A Heading Gyro Bias Online Calibration Method for Autonomous Navigation System

2021 ◽  
Author(s):  
Yunqiang Xiong ◽  
Dongmei Zhang ◽  
Chun Dong ◽  
Shuangxi Li ◽  
Hao Wu
Keyword(s):  
Navigation System ◽  
Autonomous Navigation ◽  
Calibration Method ◽  
Online Calibration ◽  
Gyro Bias ◽  
Autonomous Navigation System
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