Search

Accurate pose estimation is an essential premise for many robotic applications. In this paper, we present a novel method based on a single image of coplanar concentric circles and lines, to achieve the six degrees of freedom (6DOF) pose estimation problem. Concentric circles are proved to be useful in both disambiguating process and achieving the estimate results, and lines can take parts in heading calculation as well as the optimization parts. Numerical simulation experiments in different imaging scenarios and a set of actual flight data are taken in use to verify the effectiveness of our method.

Pose estimation via ellipse projection could achieve effective and credible results, and can be easily applied to satellite docking, aerial refueling, UAV landing and other scenes. In this paper, we derived the pose estimation from ellipse projection and firstly proposed the geometric interpretation of ambiguity. In addition, several disambiguating constraints were analyzed and a novel solution from concentric circles was proposed. A numerical simulation was taken to prove the effectiveness and advantage of our method.

This paper reports a simple novel method of effective quality factor (Q eff ) tuning by mechanical pumping. Through the red (anti-stokes) and blue (stokes) sideband activating, Q eff of the coupled MEMS resonator can be considerably adjusted. It is demonstrated that the decay time of the resonator can be greatly enhanced to 60.54 s (more than 100 times), which can be equivalent to a million-order (1.32 million) Q eff MEMS resonator. Additionally, the phenomenon of self-oscillation is observed at the blue sideband, which provides a new method of mode driving and mode locking without harmonic driving signal. Finally, the approach in this paper is also widely applicable to other MEMS/NEMS resonators, which may be useful for further researches on MEMS/NEMS sensors with high accuracy.

A pedestrian positioning method aided by magnetic heading is proposed so as to investigate a pedestrian autonomous navigation and positioning method. This method mainly employs the information from an accelerator, gyroscope and Zero Velocity Update (ZUPT) based on gait detection. Besides, geomagnetic information is used to estimate the initial heading and to calibrate the headings during the walk. The result shows that the accuracy of estimated position is effectively improved by fusing the inertial and geomagnetic information. Additionally, this paper presents the cause of magnetic heading error and its solution. By rectangular path test and the figure “8” shape path test, the proposed algorithm is proved to be valid compared with traditional pedestrian positioning method. This method owns a wide engineering application value.

This paper discusses the design of computer vision and odometer integrated autonomous navigation algorithm based on RatSLAM system for land vehicles. The research aims at testing the effectiveness of a vision/odometer bio-inspired navigation approach for land vehicle applications. Images and odometer measurements are inputted into the RatSLAM system. Odometer data can be used to improve the robustness of RatSLAM system significantly. The proposed system has been verified on real vision/odometer data collected in land vehicle tests. Campus round road experiments illustrate that the algorithm is effective and robust.

In this study, NbN thin films were deposited by reactive magnetron sputtering at different N 2 partial pressures and at room temperature. X-Ray diffraction analysis, transmission electron microscopy and atomic force microscopy were employed to characterize their phases, microstructure and surface morphology. Their microhardness and elastic modulus were evaluated using a microhardness tester and the effects of N 2 partial pressure on the phase formation, microstructure and mechanical properties of NbN thin films were investigated. The results show that there are clear effects of N 2 partial pressure on the deposition rate, phases, hardness and elastic modulus of magnetron sputtered NbN films. At a low N 2 partial pressure, the deposition rate is higher, while hcp β-Nb 2 N and fcc δ-NbN coexist in NbN films. With the increase of N 2 pressure, the deposition rate decreases and the films are single-phase fcc δNbN; accordingly, the hardness and modulus reach peak values of 36.6 GPa and 457 GPa, respectively. A further increase of the N 2 partial pressure will cause hcp e-NbN to appear in NbN films and then the hardness and modulus of films decrease.

The integration of Inertial Navigation System (INS) and Global Positioning System (GPS) is a most frequent method for land navigation. Conventional Kalman Filter (CKF) is an optimal estimation algorithm widely used in INS/GPS integration. CKF assumes that the covariance of the system process noise and measurement noise are given and constant. The performance of the CKF degrades seriously, when the GPS measurement noise changes. Researchers introduced an Innovation-based Adaptive Estimation Adaptive Kalman Filter (IAE-AKF) algorithm to keep the filter stable. However, under some extreme condition, the measurement noise may vary tremendously, which will lead to the degradation and divergence of the IAE-AKF. A robust IAE-AKF algorithm is presented in this paper, which evaluates the innovation sequence with Chi-square test and revises the abnormal innovation vector. Simulation and vehicle experiment results show that the new algorithm performs higher accuracy and robustness, and also has the ability to prevent the filtering from being diverged even in a rigorous GPS measurement environment.

Background To determine the yet unknown relation between thoracic aortic dissection (TAD) and sympathetic nervous system activity. Methods Variables such as electrocardiography, blood pressure, respiratory activity, postganglionic muscle sympathetic nerve activity （MSNA）, plasma norepinephrine, tyrosine hydroxylase–positive nerve fiber density, and growth-associated protein 43–positive nerve fiber density were detected and statistically analyzed. Results TAD Patients showed a significant lower R-R interval variance and higher blood pressure, heart rate, respiratory rate, MSNA, plasma norepinephrine (reflecting elevated sympathetic nervous system [SNS] activity), higher tyrosine hydroxylase, growth-associated protein 43–positive nerve fiber density (reflecting sympathetic sprouting and innervation) than those of the control group. Conclusions In TAD patients, both overall and regional aortic SNS activities are elevated.

Background Acute type B aortic dissection (ATBAD) is a life-threatening condition. Open chest surgical repair using a prosthetic graft has been a conventional treatment for ATBAD. During the past decade, thoracic endovascular aortic repair (TEVAR), which is considered as a less invasive and potentially safer technique, has been increasingly used to treat this condition. Evidence is needed to support the use of TEVAR for these patients. The aim of this review was to assess the efficacy of TEVAR versus conventional open surgery in patients with ATBAD. Methods For this review, we searched the Cochrane Central Register of Controlled Trials (CENTRAL) in The Cochrane Library (last searched: 2010, issue 4), MEDLINE, EMBASE, CINAHL, Web of Science, and the Chinese Biomedicine Database for clinical trials until January 18, 2011. Controlled trials in which patients with ATBAD were assigned to TEVAR or open surgical repair were included. For each outcome, we evaluated the quality of the evidence with reference to the Grading of Recommendations Assessments, Development, and Evaluation criteria. At the end, we used RevMan 5.0 software to analyze the datum. Results Five trials (318 participants) are included in this review. As determined by the Grading of Recommendations Assessments, Development, and Evaluation approach, the result quality was low for 30-day mortality and very low for other variables. TEVAR can significantly reduce the short-term mortality for ATBAD (Mantel–Haenszel fixed odds ratio [95% confidence interval]: 0.19 [0.09–0.39], P < 0.001). TEVAR cannot significantly improve postoperative complications or long-term mortality. Conclusions TEVAR can be weakly recommended as an alternative for the selective treatment of ATBAD but cannot always be used in case of surgery.

Altera Quartus II software is a comprehensive development tool that integrates Altera’s FPGA / CPLD development process involved all the tools and third-party software interface, by using this comprehensive development tool, designers can create, organize, and manage their own design. In textile machinery needle-election spending-control system, this paper proposes a design of the equal duty ratio arbitrary integer frequency divider based on FPGA. it introduces the characteristics and application domain of FPGA in brief. Then it discusses a few traditional integer frequency dividers. Finally presents the frequency division theory and circuit design of dual modulus preset decimal frequency divider based on FPGA. The frequency divider is simulated with Quartus II.

This paper presents several algorithms for estimating motion and structure parameters from long monocular image sequences by using the most apporpriate of a set of long sequence motion models. We first present a new two-view motion algorithm and then extend it to long sequence motion analysis. The two-view motion algorithm generally requires six pairs of point correspondences to give a unique solution of the motion parameters. However, when the points used for correspondences lie on a Maybank Quadric, the algorithm requires seven pairs of point correspondences to give all possible double solutions. Object-centred motion representations and models of motion described by up to the second order polynomials are analysed. Two long sequence algorithms are presented, one using interframe matches, and the other using point trajectories. The long sequence algorithms automatically find the proper model that applies to an image sequence and gives the globally optimal solution for the motion and structure parameters under the chosen model. Experimental results with several real image sequences undergoing different motions are presented to demonstrate the performance of the algorithm.

The role of public demand in innovation is the central theme of this study which tries to evaluate the weight of the Canadian public sector as: (1) first user of innovations; (2) user of inventions patented by Canadians; and (3) buyer of manufactured products. Twenty-five percent of innovations find their first use in the public sector, as do 13% of patents and 8% of the manufactured production. It does not mean that private users cannot be major first users of innovation, simultaneously or not, with public services. This public demand provides the state with significant impact on innovation, whether it applies an explicit procurement policy or not.

This paper discusses the design of extended recursive least square method based on time series analysis in order to overcome large noise and low precision of MEMS gyro. The method adopts the forgetting factor-based recursive least square which can work well even with uncertain noises. Firstly, ARMA models are used to model gyro random drifts. Secondly, variable forgetting factors enhance the robustness of extended recursive least square approach. Some experiments are carried out and the results show that the proposed method advances the performance of MEMS gyro signal de-noising. It gains better accuracy and better robustness than traditional Kalman filter.

We design a portable measurement device which can monitor electrocardiograph (ECG) and analyze arrhythmia. It is small, light, lower power, and consists of two parts: the main system and the sub. The device gets ECG signals by the electrode sticking to the chest skin. This make the device is suitable for monitoring in long time. 16-bits MCU-MSP430 is the most important part. Besides, there are amplifier circuit, filter circuit, wireless transmitting-receive circuit, data management part, keyboard and LCD display part, etc. The device can detect QRS complex and analyze ECG signals in real-time. For the MIT-BIH database and actual persons, the accuracy of monitor reaches above 99 percent of the QRS complex of ambulatory ECG signals.

The conventional Kalman filtering algorithm requires the definition of a dynamic and stochastic model, and errors of low cost MEMS-IMU are likely to vary temporally. So the conventional Kalman filter exists limitation in MEMS-IMU/GPS integrated navigation. This paper presented the use of multiple model adaptive estimation(MMAE) where multiple Kalman filters were run in parallel using different dynamic or stochastic models in MEMS-IMU/GPS integrated navigation. And the modified multiple model Kalman filter was used in order to solve the limitation of multiple model adaptive estimation(MMAE). Using static tests, the algorithm designed was validated. The test results show that the modified multiple model Kalman filter can improve performance of MEMS-IMU/GPS integrated navigation system, compared to the conventional Kalman filtering algorithm. And using the designed algorithm, the positioning accuracy is better than 5m and velocity accuracy is better than 0.1m/ s2, and the attitude errors are less than 0.5 degrees on the static condition.

A identification in a nonlinear stochastic system - strapdown inertial navigation system is addressed. A new online-identification algorithm of odometer's scale factor is proposed. From zero velocity update (ZUPT), the velocity errors in inertial navigation system propagate in the Schuler loops, and based the slow-varying property of velocity errors, the algorithm identifies the odometer's scale factor using the changes of velocity during a short time. A tracking differentiator and a fadeout memory LMS algorithm is adopted in the identification to make the algorithm more practicable. The algorithm can track the odometer's scale factor varying with time, and therefore be suitable for navigation case in which a vehicle runs a long time and roads vary a lot. Simulation indicates that this new algorithm can identify the odometer's scale factor fast with small errors, so as to improve the accuracy of navigation.

This paper discusses the design of SINS/GPS adaptive Kalman filtering algorithm based on motion constraints for land vehicle applications. The algorithm adopts the architecture of tight integration which can continue to work even with no more than four GPS satellites. The vehicle motion constraints enhance the observation of the integrated navigation when satellite is outage. Adaptive Kalman filter with forgetting factor improves robustness of the integrated system. Some experiments are carried out and the results show that the proposed algorithm advances the performance of SINS/GPS integrated system. It gains better position accuracy 4.86 times and better velocity accuracy 1.23 times than traditional Kalman filtering algorithm.

Ultrasonic amplitude transformer bar is an important part in the power ultrasonic vibration systems. With an application example, a half-wavelength amplitude transformer bar of conical type is designed by analytical method. The freedom modal analysis on the transformer bar was made with finite element analysis software ANSYS, and the natural frequency of transformer bar was obtained. Finally the transformer bar with attached tool was amended by method of finite element analysis, and the purpose of amendment can make the certain natural frequency equal to the operating frequency of vibration system, so as to make sure that transformer bar can lengthways resonate reliably when it is stimulated.

An adaptive radical basis function (RBF) neural network PID control scheme for X-Y position table is proposed by the paper. Firstly, X-Y position table model is established, controller based on neutral network is used to learn adaptive and compensate uncertainty model of X-Y position table, neutral network is used to study model. PID neural network controller base on augmented variable method is designed. PID controller is used as assistant direction error controller, neural network parameters base on stochastic gradient algorithm can be adjust adaptive on line. The simulation results show that the presented controller has important engineering value.