scholarly journals Automatic Estimation of Dynamic Lever Arms for a Position and Orientation System

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4230 ◽  
Author(s):  
Qiangwen Fu ◽  
Sihai Li ◽  
Yang Liu ◽  
Qi Zhou ◽  
Feng Wu
Keyword(s):  
Estimation Method ◽  
Measurement Unit ◽  
Valuable Insight ◽  
Differential Gps ◽  
Distribution Method ◽  
Lever Arm ◽  
Automatic Estimation ◽  
Orientation System ◽  
Position And Orientation ◽  
Stabilized Platform

An inertially stabilized platform (ISP) is generally equipped with a position and orientation system (POS) to isolate attitude disturbances and to focus surveying sensors on interesting targets. However, rotation of the ISP will result in a time-varying lever arm between the measuring center of the inertial measurement unit (IMU) and the phase center of the Global Positioning System (GPS) antenna, making it difficult to measure and provide compensation. To avoid the complexity of manual measurement and improve surveying efficiency, we propose an automatic estimation method for the dynamic lever arm. With the aid of the ISP encoder data, we decompose the variable lever arm into two constant lever arms to be estimated on line. With a complete 21-dimensional state Kalman filter, we accurately and simultaneously accomplish navigation and dynamic lever arm calibration. Our observability analysis provides a valuable insight into the conditions under which the lever arms can be estimated, and we use the error distribution method to reveal which error sources are the most influential. The simulation results demonstrate that the dynamic lever arm can be estimated to within [0.0104; 0.0110; 0.0178] m, an accuracy that is equivalent to the positioning accuracy of Carrier-phase Differential GPS (CDGPS).

scholarly journals A Novel Separated Position and Orientation System Integrated with Inertially Stabilized Platform

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Yanshun Zhang ◽  
Shuangji Feng ◽  
Zhanqing Wang ◽  
Xiaopeng Xi ◽  
Ming Li
Keyword(s):  
Inertial Sensors ◽  
Orientation System ◽  
Imaging Payloads ◽  
Position And Orientation ◽  
Velocity Motion ◽  
Stabilized Platform ◽  
Application Requirements ◽  
Inertially Stabilized Platform ◽  
Centralized System ◽  
Effective Function

Considering the application requirements of independent imaging payloads design, a novel scheme of separated position and orientation system (POS) is proposed, in which the high-precision inertial sensors of traditional centralized POS fixed on the imaging payloads are mounted on three gimbals of the inertially stabilized platform (ISP), respectively, and make them integrated. Then, the kinematics model of the ISP system is built to transmit the inertial information measured by separated inertial sensors mounted on ISP gimbals and flight body to the imaging payloads, calculating the position and attitude of the imaging payloads to achieve the function of separated POS. Based on the model, a series of simulations indicate that the precision difference between separated system and centralized system is ignorable under the condition of angular motion and variable velocity motion. Besides the effective function equal to traditional centralized system, the separated POS enhances the integration with the ISP. Moreover, it improves the design independence of the imaging payloads significantly.

scholarly journals End-Effector Pose Estimation in Complex Environments Using Complementary Enhancement and Adaptive Fusion of Multisensor

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Mingrui Luo ◽  
En Li ◽  
Rui Guo ◽  
Jiaxin Liu ◽  
Zize Liang
Keyword(s):  
Kalman Filter ◽  
Pose Estimation ◽  
Unscented Kalman Filter ◽  
Rbf Neural Network ◽  
Estimation Error ◽  
Estimation Method ◽  
Original Data ◽  
Measurement Unit ◽  
Complex Environments ◽  
End Effector

Redundant manipulators are suitable for working in narrow and complex environments due to their flexibility. However, a large number of joints and long slender links make it hard to obtain the accurate end-effector pose of the redundant manipulator directly through the encoders. In this paper, a pose estimation method is proposed with the fusion of vision sensors, inertial sensors, and encoders. Firstly, according to the complementary characteristics of each measurement unit in the sensors, the original data is corrected and enhanced. Furthermore, an improved Kalman filter (KF) algorithm is adopted for data fusion by establishing the nonlinear motion prediction of the end-effector and the synchronization update model of the multirate sensors. Finally, the radial basis function (RBF) neural network is used to adaptively adjust the fusion parameters. It is verified in experiments that the proposed method achieves better performances on estimation error and update frequency than the original extended Kalman filter (EKF) and unscented Kalman filter (UKF) algorithm, especially in complex environments.

scholarly journals Online Estimation of Short-Circuit Fault Level in Active Distribution Network

2020 ◽  
Vol 10 (11) ◽  
pp. 3812
Author(s):  
Xiaohui Wang ◽  
Peng Wang ◽  
Yunbo Wang ◽  
Fang Shi
Keyword(s):  
Equivalent Circuit ◽  
Short Circuit ◽  
Distribution Network ◽  
Estimation Method ◽  
Short Circuit Current ◽  
Distribution Networks ◽  
Measurement Unit ◽  
Online Estimation ◽  
Active Distribution Network ◽  
Short Circuit Fault

The potential short-circuit current in active distribution network features time-variance with the increasing distributed generations. This feature makes the online estimation of fault level necessary. In this paper, a novel online estimation method is proposed to be implemented by either phasor measurement unit (PMU) or the measurements from protection relays. The equivalent circuit of the radial distribution network with distributed generators (DGs), e.g., wind turbines and photovoltaic cells, is derived with necessary simplifications. The natural disturbances downstream are used to evaluate the parameters of the equivalent circuit so that the potential fault level can be estimated in advance of the actual fault occurrence. A fuzzy logic identifier is presented to rank the confidence of the measurements incurred by the disturbance and to distinguish the qualified disturbance to launch the estimation. The mechanism based on multi-measurements and confidence indices was applied, to improve the accuracy. A typical distribution network in the United Kingdom (UK) with DGs was taken, as an example, to validate the proposed method under various load fluctuation. The results confirm the effectiveness of the proposed method, which is suitable for online estimation of short-circuit fault level in active distribution networks.

scholarly journals IMU-Based Online Kinematic Calibration of Robot Manipulator

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Guanglong Du ◽  
Ping Zhang
Keyword(s):  
Kalman Filter ◽  
Robot Manipulator ◽  
Experimental Studies ◽  
Estimation Method ◽  
Kinematic Parameter ◽  
Corner Detection ◽  
Measurement Unit ◽  
Robot Calibration ◽  
Self Calibration ◽  
Calibration Methods

Robot calibration is a useful diagnostic method for improving the positioning accuracy in robot production and maintenance. An online robot self-calibration method based on inertial measurement unit (IMU) is presented in this paper. The method requires that the IMU is rigidly attached to the robot manipulator, which makes it possible to obtain the orientation of the manipulator with the orientation of the IMU in real time. This paper proposed an efficient approach which incorporates Factored Quaternion Algorithm (FQA) and Kalman Filter (KF) to estimate the orientation of the IMU. Then, an Extended Kalman Filter (EKF) is used to estimate kinematic parameter errors. Using this proposed orientation estimation method will result in improved reliability and accuracy in determining the orientation of the manipulator. Compared with the existing vision-based self-calibration methods, the great advantage of this method is that it does not need the complex steps, such as camera calibration, images capture, and corner detection, which make the robot calibration procedure more autonomous in a dynamic manufacturing environment. Experimental studies on a GOOGOL GRB3016 robot show that this method has better accuracy, convenience, and effectiveness than vision-based methods.

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