Relative Distance Error Research Articles

A Switched Based Control Strategy for Target Tracking of Autonomous Robotic Vehicles using Range-only Measurements

AbstractIn this paper we address the pursuing or target tracking problem where an autonomous robotic vehicle is required to move towards a maneuvering target using range-only measurements. A new switched based control strategy is proposed to solve the pursuing problem that can be described as comprising a continuous cycle of two distinct phases: i) the determination of the bearing, and ii) following the direction computed in the previous step while the range is decreasing. We provide conditions under which the switched closed-loop system achieves convergence of the relative distance error to a small neighborhood around zero. Simulation results are presented and discussed.

Leukocyte nucleus segmentation and nucleus lobe counting

BackgroundLeukocytes play an important role in the human immune system. The family of leukocytes is comprised of lymphocytes, monocytes, eosinophils, basophils, and neutrophils. Any infection or acute stress may increase or decrease the number of leukocytes. An increased percentage of neutrophils may be caused by an acute infection, while an increased percentage of lymphocytes can be caused by a chronic bacterial infection. It is important to realize an abnormal variation in the leukocytes. The five types of leukocytes can be distinguished by their cytoplasmic granules, staining properties of the granules, size of cell, the proportion of the nuclear to the cytoplasmic material, and the type of nucleolar lobes. The number of lobes increased when leukemia, chronic nephritis, liver disease, cancer, sepsis, and vitamin B12 or folate deficiency occurred. Clinical neutrophil hypersegmentation has been widely used as an indicator of B12 or folate deficiency.Biomedical technologists can currently recognize abnormal leukocytes using human eyes. However, the quality and efficiency of diagnosis may be compromised due to the limitations of the biomedical technologists' eyesight, strength, and medical knowledge. Therefore, the development of an automatic leukocyte recognition system is feasible and necessary. It is essential to extract the leukocyte region from a blood smear image in order to develop an automatic leukocyte recognition system. The number of lobes increased when leukemia, chronic nephritis, liver disease, cancer, sepsis, and vitamin B12 or folate deficiency occurred. Clinical neutrophil hypersegmentation has been widely used as an indicator of B12 or folate deficiency.ResultsThe purpose of this paper is to contribute an automatic leukocyte nuclei image segmentation method for such recognition technology. The other goal of this paper is to develop the method of counting the number of lobes in a cell nucleus. The experimental results demonstrated impressive segmentation accuracy.ConclusionsInsensitive to the variance of images, the LNS (Leukocyte Nuclei Segmentation) method functioned well to isolate the leukocyte nuclei from a blood smear image with much better UR (Under Segmentation Rate), ER (Overall Error Rate), and RDE (Relative Distance Error). The presented LC (Lobe Counting) method is capable of splitting leukocyte nuclei into lobes. The experimental results illuminated that both methods can give expressive performances. In addition, three advanced image processing techniques were proposed as weighted Sobel operator, GDW (Gradient Direction Weight), and GBPD (Genetic-based Parameter Detector).

A 16$\, \times $16 Pixel Distance Sensor With In-Pixel Circuitry That Tolerates 150 klx of Ambient Light

A time-of-flight depth sensor is presented employing a correlation based concept. The pixels are able to suppress contributions of ambient light up to 150 klx autonomously and directly in the electronic circuits consuming only 2 μA, each. All 16 × 16 pixels capture the depth information simultaneously at maximally 16 frames per second using an external A/D converter (ADC). Additionally, an embedded 12-bit ADC can be used for converting the analog output values of the pixels to the digital domain at lower frame rates. Distance measurements in a range of 0-3.2 m show standard deviations in the centimeter range and a linearity error within -1/+2 cm. The influence of extraneous light is expressed as a relative distance error which is also in the centimeter range. A complete impression of the sensor system is given by discussing the pixel circuits, the ADC design, the design of the modulated light source providing 0.9 W optical power in the near infrared, and the auxiliary setup including an FPGA board. Additionally, a sensor model is provided to predict the measurement error due to stochastic sources. Three-dimensional snapshots as well as a comparison with state-of-the-art sensors and products complete the paper.

String formations of multiple vehicles via pursuit strategy

String formations of multiple vehicles where all vehicles involved are linked by a virtual thread are studied. Such a formation is useful for a fleet of vehicles driving in a platoon sequence on a road. Our approach differs from most other formation algorithms by separating distance and bearing between neighbouring vehicles. We treat the string formation as a natural consequence of a pursuit game. The proposed pursuit strategy is a distributed algorithm and uses only the relative distance error of the vehicle in front. Stable states are presented and the stability of the algorithm is proven. Finally, some simulation examples are given to demonstrate the practical application of the theoretical results.

Distance determination for RAVE stars using stellar models

<i>Aims. <i/>We develop a method for deriving distances from spectroscopic data and obtaining full 6D phase-space coordinates for the RAVE survey's second data release.<i>Methods. <i/>We used stellar models combined with atmospheric properties from RAVE (effective temperature, surface gravity and metallicity) and (<i>J<i/>-<i>K<i/><sub>s<sub/>) photometry from archival sources to derive absolute magnitudes. In combination with apparent magnitudes, sky coordinates, proper motions from a variety of sources and radial velocities from RAVE, we are able to derive the full 6D phase-space coordinates for a large sample of RAVE stars. This method is tested with artificial data, Hipparcos trigonometric parallaxes and observations of the open cluster M 67.<i>Results. <i/>When we applied our method to a set of 16 146 stars, we found that 25% (4037) of the stars have relative (statistical) distance errors of <i><<i/>35%, while 50% (8073) and 75% (12 110) have relative (statistical) errors smaller than 45% and 50%, respectively. Our various tests show that we can reliably estimate distances for main-sequence stars, but there is an indication of potential systematic problems with giant stars owing to uncertainties in the underlying stellar models. For the main-sequence star sample (defined as those with log(<i>g<i/>) > 4), 25% (1744) have relative distance errors <i><<i/>31%, while 50% (3488) and 75% (5231) have relative errors smaller than 36% and 42%, respectively. Our full dataset shows the expected decrease in the metallicity of stars as a function of distance from the Galactic plane. The known kinematic substructures in the <i>U<i/> and <i>V<i/> velocity components of nearby dwarf stars are apparent in our dataset, confirming the accuracy of our data and the reliability of our technique. We provide independent measurements of the orientation of the <i>UV<i/> velocity ellipsoid and of the solar motion, and they are in very good agreement with previous work.<i>Conclusions. <i/>The distance catalogue for the RAVE second data release is available at http://www.astro.rug.nl/~rave, and will be updated in the future to include new data releases.

Assessment of optical localizer accuracy for computer aided surgery systems

The technology for localization of surgical tools with respect to the patient's reference coordinate system in three to six degrees of freedom is one of the key components in computer aided surgery. Several tracking methods are available, of which optical tracking is the most widespread in clinical use. Optical tracking technology has proven to be a reliable method for intra-operative position and orientation acquisition in many clinical applications; however, the accuracy of such localizers is still a topic of discussion.In this paper, the accuracy of three optical localizer systems, the NDI Polaris P4, the NDI Polaris Spectra (in active and passive mode) and the Stryker Navigation System II camera, is assessed and compared critically.Static tests revealed that only the Polaris P4 shows significant warm-up behavior, with a significant shift of accuracy being observed within 42 minutes of being switched on. Furthermore, the intrinsic localizer accuracy was determined for single markers as well as for tools using a volumetric measurement protocol on a coordinate measurement machine. To determine the relative distance error within the measurement volume, the Length Measurement Error (LME) was determined at 35 test lengths. As accuracy depends strongly on the marker configuration employed, the error to be expected in typical clinical setups was estimated in a simulation for different tool configurations.The two active localizer systems, the Stryker Navigation System II camera and the Polaris Spectra (active mode), showed the best results, with trueness values (mean ± standard deviation) of 0.058 ± 0.033 mm and 0.089 ± 0.061 mm, respectively. The Polaris Spectra (passive mode) showed a trueness of 0.170 ± 0.090 mm, and the Polaris P4 showed the lowest trueness at 0.272 ± 0.394 mm with a higher number of outliers than for the other cameras.The simulation of the different tool configurations in a typical clinical setup revealed that the tracking error can be estimated to be 1.02 mm for the Polaris P4, 0.64 mm for the Polaris Spectra in passive mode, 0.33 mm for the Polaris Spectra in active mode, and 0.22 mm for the Stryker Navigation System II camera.

Automatic Segmentation of Calcifications in Intravascular Ultrasound Images Using Snakes and the Contourlet Transform

It is valuable to detect calcifications in intravascular ultrasound images for studies of coronary artery diseases. An image segmentation method based on snakes and the Contourlet transform is proposed to automatically and accurately detect calcifications. With the Contourlet transform, an original image is decomposed into low-pass bands and band-pass directional sub-bands. The 2-D Renyi's entropy is used to adaptively threshold the low-pass bands in a multiresolution hierarchy to determine regions-of-interest (ROIs). Then a mean intensity ratio, reflecting acoustic shadowing, is presented to classify calcifications from noncalcifications and obtain initial contours of calcifications. The anisotropic diffusion is used in bandpass directional sub-bands to suppress noise and preserve calcific edges. Finally, the contour deformation in the boundary vector field is used to obtain final contours of calcifications. The method was evaluated via 60 simulated images and 86 in vivo images. It outperformed a recently proposed method, the Santos Filho method, by 2.76% and 14.53%, in terms of the sensitivity and specificity of calcification detection, respectively. The area under the receiver operating characteristic curve increased by 0.041. The relative mean distance error, relative difference degree, relative arc difference, relative thickness difference and relative length difference were reduced by 5.73%, 19.79%, 11.62%, 12.06% and 20.51%, respectively. These results reveal that the proposed method can automatically and accurately detect calcifications and delineate their boundaries. (E-mail: yywang@fudan.edu.cn)

Localization and tracking of phonating finless porpoises using towed stereo acoustic data-loggers

Cetaceans produce sound signals frequently. Usually, acoustic localization of cetaceans was made by cable hydrophone arrays and multichannel recording systems. In this study, a simple and relatively inexpensive towed acoustic system consisting of two miniature stereo acoustic data-loggers is described for localization and tracking of finless porpoises in a mobile survey. Among 204 porpoises detected acoustically, 34 individuals (approximately 17%) were localized, and 4 of the 34 localized individuals were tracked. The accuracy of the localization is considered to be fairly high, as the upper bounds of relative distance errors were less than 41% within 173 m. With the location information, source levels of finless porpoise clicks were estimated to range from 180 to 209 dB re 1 microPa pp at 1 m with an average of 197 dB (N=34), which is over 20 dB higher than that estimated previously from animals in enclosed waters. For the four tracked porpoises, two-dimensional swimming trajectories relative to the moving survey boat, absolute swimming speed, and absolute heading direction are deduced by assuming the animal movements are straight and at constant speed in the segment between two consecutive locations.

Formation Geometry Center based Formation Controller Design using Lyapunov Stability Theorem

New formation flight controller for unmanned aerial vehicles is proposed. A behavioral decentralized control approach called formation geometry center control is adopted. Trajectory tracking as well as formation geometry keeping are the purpose of the formation flight, and therefore two controllers are designed: a trajectory tracking controller for reference trajectory tracking, and a position controller for formation geometry keeping. Each controller is designed using Lyapunov stability theorem to guarantee the asymptotic stability. Formation flight controller is finally obtained by combining the trajectory tracking controller and the formation geometry keeping controller using a weighting parameter that depends on the relative distance error between unmanned aerial vehicles. Numerical simulations are performed to validate the performance of the proposed controller.

Improved iterative pose estimation algorithm using three-dimensional feature points

In a real-time vision navigation system, an accurate and fast convergent pose estimation algorithm is required for the video guidance sensor. The orthogonal iteration (OI) algorithm is fast and globally convergent, but its results have a large translation error at a close range, and sometimes it fails to give a correct rotation matrix when the data are severely corrupted, when using the 3-D feature points. When the rotation matrix solution in the OI algorithm has been refined, an efficient pose estimation algorithm is derived. Simulation of the improved algorithm shows that the rotation matrix is always proper, which in turn improves the accuracy of the translation vector. The noise resistance and the outlier tolerance are enhanced by using the improved algorithm. The two algorithms are applied to our experimental system for an unmanned vehicle rendezvous and docking simulation separately. The comparison experiments show that the relative distance error is less than 0.28% from 1.5 to 5 m, and the rotation angle error is within ±0.7 deg in 5 m using the improved algorithm. These are better than the results using the OI algorithm.

Motion Error Correction Scheme Using the Spatial Doppler Characteristics of the In-Scene Target in the SAR Imaging System

The success of target reconstruction in the SAR(Synthetic Aperture Radar) imaging system is greatly dependent on coherent detection. Incoherent detection appears as a multiplicative phase error to echoed signal, which consequently causes fatal degradations such as fading or dislocation of target image. In this paper, we propose a motion error correction scheme using an in-scene target to compensate for relative distance error between the radar and the target. We start by modeling from a wave equation for one point target, and then derive the complex motion error from extended overall echoed data. The proposed algorithm is also good for the correction of relatively large motion error because it can be applied repeatedly, and it is converged after each iteration. We use the spatial Doppler characteristics of the strong in-scene target to retrieve motion error, thus, we only used the partial spectral echo data corresponding to the strong in-scene target. By doing this, we can reduce computational loads and the number of iterations for the large motion error. We verify the performance of the proposed algorithm by applying it to the simulated spotlight-mode SAR data.

A new family of distance indicator relations for elliptical galaxies

A new family of distance indicator relations for elliptical galaxies is described. Distance-dependent quantities are expressed as distance-independent combinations of the mean surface brightness and a color, or any other metallicity indicator. Preliminary results based on published data indicate that the typical relative distance errors to individual galaxies derived from new relations are about 25 percent, and the accuracy of about 15 percent may be achievable with more homogeneous data sets. This is comparable to the accuracy obtained from the Tully-Fisher and D(n)-sigma relations. The necessary data are derived from photometry only and thus can be obtained relatively quickly for large numbers of galaxies. 30 refs.