scholarly journals Spacecraft Pose Estimation Based on Different Camera Model

2020 ◽  
Author(s):  
Li-Dong Mo ◽  
Guan-Xin Chi ◽  
Zhen-Qing Zhao
Keyword(s):  
Pose Estimation ◽  
Optimal Solution ◽  
Estimation Algorithm ◽  
Measurement Model ◽  
Depth Information ◽  
Perspective Projection ◽  
Camera Model ◽  
Projection Model ◽  
Simulation Results ◽  
Symmetrical Points

Abstract Spacecraft pose estimation is an important technology for spacecraft to maintain or change its orientation in space. For spacecraft pose estimation, when two spacecraft are relatively far away, the depth information of the space point is less than that of measuring distance, so that the camera model can be seen as a weak perspective projection model. In this paper, a spacecraft pose estimation algorithm based on four symmetrical points of the spacecraft outline is proposed. Analytical solution of spacecraft pose is obtained by solving the weak perspective projection model, which can meet the requirements of the measurement model when there is a long measurement distance. Optimal solution is obtained from the weak perspective projection model to the perspective projection model, which can meet the measurement requirement when the measuring distance is close. The simulation results show that the proposed algorithm can get better results even though the noise is large.

scholarly journals Assistive Grasping Based on Laser-point Detection with Application to Wheelchair-mounted Robotic Arms

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 303 ◽  
Author(s):  
Ming Zhong ◽  
Yanqiang Zhang ◽  
Xi Yang ◽  
Yufeng Yao ◽  
Junlong Guo ◽  
...  
Keyword(s):  
Pose Estimation ◽  
Estimation Error ◽  
Estimation Algorithm ◽  
Experimental Results ◽  
Depth Information ◽  
Laser Pointer ◽  
Point Interactions ◽  
Robotic Arms ◽  
Key Steps ◽  
Point Detection

As the aging of the population becomes more severe, wheelchair-mounted robotic arms (WMRAs) are gaining an increased amount of attention. Laser pointer interactions are an attractive method enabling humans to unambiguously point out objects and pick them up. In addition, they bring about a greater sense of participation in the interaction process as an intuitive interaction mode. However, the issue of human–robot interactions remains to be properly tackled, and traditional laser point interactions still suffer from poor real-time performance and low accuracy amid dynamic backgrounds. In this study, combined with an advanced laser point detection method and an improved pose estimation algorithm, a laser pointer is used to facilitate the interactions between humans and a WMRA in an indoor environment. Assistive grasping using a laser selection consists of two key steps. In the first step, the images captured using an RGB-D camera are pre-processed, and then fed to a convolutional neural network (CNN) to determine the 2D coordinates of the laser point and objects within the image. Meanwhile, the centroid coordinates of the selected object are also obtained using the depth information. In this way, the object to be picked up and its location are determined. The experimental results show that the laser point can be detected with almost 100% accuracy in a complex environment. In the second step, a compound pose-estimation algorithm aiming at a sparse use of multi-view templates is applied, which consists of both coarse- and precise-matching of the target to the template objects, greatly improving the grasping performance. The proposed algorithms were implemented on a Kinova Jaco robotic arm, and the experimental results demonstrate their effectiveness. Compared with commonly accepted methods, the time consumption of the pose generation can be reduced from 5.36 to 4.43 s, and synchronously, the pose estimation error is significantly improved from 21.31% to 3.91%.

scholarly journals Optimal Decision-Making to Charge Electric Vehicles in Heterogeneous Networks: Stackelberg Game Approach

Energies ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 325 ◽  
Author(s):  
Shijun Chen ◽  
Huwei Chen ◽  
Shanhe Jiang
Keyword(s):  
Electric Vehicles ◽  
Heterogeneous Networks ◽  
Demand Uncertainty ◽  
Stackelberg Game ◽  
Optimal Solution ◽  
Stackelberg Equilibrium ◽  
Optimal Decision ◽  
Charging Station ◽  
Simulation Results ◽  
Grid Operators

Electric vehicles (EVs) are designed to improve the efficiency of energy and prevent the environment from being polluted, when they are widely and reasonably used in the transport system. However, due to the feature of EV’s batteries, the charging problem plays an important role in the application of EVs. Fortunately, with the help of advanced technologies, charging stations powered by smart grid operators (SGOs) can easily and conveniently solve the problems and supply charging service to EV users. In this paper, we consider that EVs will be charged by charging station operators (CSOs) in heterogeneous networks (Hetnet), through which they can exchange the information with each other. Considering the trading relationship among EV users, CSOs, and SGOs, we design their own utility functions in Hetnet, where the demand uncertainty is taken into account. In order to maximize the profits, we formulate this charging problem as a four-stage Stackelberg game, through which the optimal strategy is studied and analyzed. In the Stackelberg game model, we theoretically prove and discuss the existence and uniqueness of the Stackelberg equilibrium (SE). Using the proposed iterative algorithm, the optimal solution can be obtained in the optimization problem. The performance of the strategy is shown in the simulation results. It is shown that the simulation results confirm the efficiency of the model in Hetnet.

A Novel Symbol Rate Estimation Algorithm for Phase Modulating Signals in Wireless Communications

2013 ◽  
Vol 443 ◽  
pp. 392-396
Author(s):  
Peng Zhou ◽  
Chi Sheng Li
Keyword(s):  
Signal To Noise Ratio ◽  
Estimation Algorithm ◽  
Frequency Resolution ◽  
Phase Shift Keying ◽  
Phase Jump ◽  
Rate Estimation ◽  
Awgn Channel ◽  
Symbol Rate ◽  
Shift Keying ◽  
Simulation Results

In this paper, we proposed a new symbol rate estimation algorithm for phase shift keying (PSK) and qua drawtube amplitude modulation (QAM) signals in AWGN channel First we constructe a delay-multiplied signal, from which we obtaine the modulated information. Then we calculated the instantaneous autocorrelation of the delay-multiplied signal to pick out the phase jump. To eliminate the restriction of frequency resolution in fast Fourier transform, we performed a Chirp-Z transform to find out the exact spectral line which represente the symbol rate of the signal to be analyzed. Compared with the existing algorithms, it is a simple solution that has a better performance and accuracy in low signal-to-noise-ratio channel conditions. Simulation results show that the probability of relative estimating deviation below 0.1% reaches 100% and the average and standard variance of absolute estimation deviation are at the magnitude of 10-2 when SNR is over 2dB.

scholarly journals Novel MARG-Sensor Orientation Estimation Algorithm Using Fast Kalman Filter

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Siwen Guo ◽  
Jin Wu ◽  
Zuocai Wang ◽  
Jide Qian
Keyword(s):  
Kalman Filter ◽  
Process Model ◽  
Attitude Determination ◽  
Angular Rate ◽  
Estimation Algorithm ◽  
Measurement Model ◽  
Estimation Accuracy ◽  
Orientation Estimation ◽  
Kinematic Equation ◽  
Sensor Orientation

Orientation estimation from magnetic, angular rate, and gravity (MARG) sensor array is a key problem in mechatronic-related applications. This paper proposes a new method in which a quaternion-based Kalman filter scheme is designed. The quaternion kinematic equation is employed as the process model. With our previous contributions, we establish the measurement model of attitude quaternion from accelerometer and magnetometer, which is later proved to be the fastest (computationally) one among representative attitude determination algorithms of such sensor combination. Variance analysis is later given enabling the optimal updating of the proposed filter. The algorithm is implemented on real-world hardware where experiments are carried out to reveal the advantages of the proposed method with respect to conventional ones. The proposed approach is also validated on an unmanned aerial vehicle during a real flight. Results show that the proposed one is faster than any other Kalman-based ones and even faster than some complementary ones while the attitude estimation accuracy is maintained.

BLIND JOINT ANGLE, FREQUENCY AND POLARIZATION ESTIMATION FOR POLARIZATION SENSITIVE ARRAY USING QUADRILINEAR DECOMPOSITION

2013 ◽  
Vol 22 (02) ◽  
pp. 1250091
Author(s):  
XIAOFEI ZHANG ◽  
CHEN CHEN ◽  
YINGJIE HUANG ◽  
HAILANG WU ◽  
JIANFENG LI ◽  
...  
Keyword(s):  
Joint Angle ◽  
Estimation Algorithm ◽  
Low Rank ◽  
Fundamental Result ◽  
Parameter Estimation Problem ◽  
Data Decomposition ◽  
Multiple Parameters ◽  
Polarization Sensitive Array ◽  
Polarization Estimation ◽  
Simulation Results

This paper links the polarization-sensitive-array parameter estimation problem to the quadrilinear model. Exploiting this link, it derives a blind joint angle, frequency and polarization estimation algorithm. The simulation results reveal that the proposed algorithm has better angle, frequency and polarization estimation performance than ESPRIT. This algorithm relies on a fundamental result of the uniqueness of low-rank four-way data decomposition. Furthermore, the proposed algorithm does not require pairing among multiple parameters. Simulation results illustrate performance of this algorithm.

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