Position Calibration Research Articles

Mobile Laser Scanning for Estimating Tree Stem Diameter Using Segmentation and Tree Spine Calibration

Mobile laser scanning (MLS) could make forest inventories more efficient, by using algorithms that automatically derive tree stem center positions and stem diameters. In this work we present a novel method for calibration of the position for laser returns based on tree spines derived from laser data. A first calibration of positions was made for sequential laser scans and further calibrations of laser returns were possible after segmentation, in which laser returns were associated to individual tree stems. The segmentation made it possible to model tree stem spines (i.e., center line of tree stems). Assumptions of coherent tree spine positions were used for correcting laser return positions on the tree stems, thereby improving estimation of stem profiles (i.e., stem diameters at different heights from the ground level). The method was validated on six 20-m radius field plots. Stem diameters were estimated with a Root-Mean-Square-Error (RMSE) of 1 cm for safely linked trees (maximum link distance of 0.5 m) and with a restriction of a minimum amount of data from height intervals for supporting circle estimates. The accuracy was high for plot level estimates of basal area-weighted mean stem diameter (relative RMSE 3.4%) and basal area (relative RMSE 8.5%) because of little influence of small trees (i.e., aggregation of individual trees). The spine calibration made it possible to derive 3D stem profiles also from 3D laser data calculated from sensor positions with large errors because of disturbed below canopy signals from global navigation satellite systems.

Three-Dimensional Point Cloud Reconstruction and Morphology Measurement Method for Greenhouse Plants Based on the Kinect Sensor Self-Calibration

Plant morphological data are an important basis for precision agriculture and plant phenomics. The three-dimensional (3D) geometric shape of plants is complex, and the 3D morphology of a plant changes relatively significantly during the full growth cycle. In order to make high-throughput measurements of the 3D morphological data of greenhouse plants, it is necessary to frequently adjust the relative position between the sensor and the plant. Therefore, it is necessary to frequently adjust the Kinect sensor position and consequently recalibrate the Kinect sensor during the full growth cycle of the plant, which significantly increases the tedium of the multiview 3D point cloud reconstruction process. A high-throughput 3D rapid greenhouse plant point cloud reconstruction method based on autonomous Kinect v2 sensor position calibration is proposed for 3D phenotyping greenhouse plants. Two red–green–blue–depth (RGB-D) images of the turntable surface are acquired by the Kinect v2 sensor. The central point and normal vector of the axis of rotation of the turntable are calculated automatically. The coordinate systems of RGB-D images captured at various view angles are unified based on the central point and normal vector of the axis of the turntable to achieve coarse registration. Then, the iterative closest point algorithm is used to perform multiview point cloud precise registration, thereby achieving rapid 3D point cloud reconstruction of the greenhouse plant. The greenhouse tomato plants were selected as measurement objects in this study. Research results show that the proposed 3D point cloud reconstruction method was highly accurate and stable in performance, and can be used to reconstruct 3D point clouds for high-throughput plant phenotyping analysis and to extract the morphological parameters of plants.

Heavy-ion Radiotherapy Rotating Gantry Calibration for Improving Patient Positioning Accuracy

In heavy-ion radiotherapy, accurate patient positioning is necessary for treatment accuracy. For this purpose, calibration of the X-ray imaging device position is indispensable. However, because positional repeatability of a calibration phantom in the rotating gantry affects the calibration result, it is not possible to calibrate using known 3-D positions of iron balls. Hence, instead of using the positions of the iron balls, we developed an X-ray tube position calibration method using the position and rotation of the FPD measured by a laser tracker. In the proposed method, the positions of the X-ray tube and iron balls are adjusted so that the distance between the position to be projected of each iron ball and the detected position (reprojection error) is minimized. In the rotating gantry calibration, multiple images are taken while changing the gantry angle, but since the position of the calibration phantom during imaging is unchanged, it is possible to represent the 3-D iron ball position with common parameters among the images. As described above, bundle adjustment can be cited as a method for calculating the position of the 3-D point and the imaging system parameter from the corresponding point between the multiple view images. The principle is to adjust all the unknown parameters so that the projected iron ball position on the image by the estimated parameters matches as closely as possible the iron ball position detected from the image. In this paper, we propose a rotating gantry calibration method based on bundle adjustment. First, by approximating the position of the X-ray tube at which the reprojection error becomes small as a function of the iron ball position of the calibration phantom, the number of parameters is reduced and the position of the iron ball is optimized. Next, the positions of the iron balls are fixed and the position of the X-ray tube is optimized. At this time, by analytically calculating the solution of two axes out of three axes where reprojection error becomes the minimum, efficient search is executed as a 1-D optimization problem. A head phantom was imaged while rotating the gantry in increments of 15 degrees, patient positioning was performed at each angle, and how the result changes with or without calibration was evaluated. For the head phantom study, the Euclidean distance patient positioning error of each angle with respect to the positioning result at the reference angle was 0.62 ± 0.21 mm (mean ± SD) and the maximum was about 1.0 mm without calibration, but with calibration, these values became 0.09 ± 0.03 mm and 0.2 mm. We proposed an automatic calibration method for rotating gantry heavy-ion radiotherapy. By using the method, the patient positioning accuracy of the rotating gantry was improved.Abstract 3625; Table 1Patient positioning error with / without calibrationPatient positioning error [mm]Maximum error [mm]without calibration0.62(±0.21)0.96with calibration0.09(±0.03)0.20 Open table in a new tab

Smart Insole-Based Indoor Localization System for Internet of Things Applications

With the development of Internet of Things (IoT), indoor localization has been a research focus in recent years. For inertial measurement unit (IMU)-based indoor localization method, zero velocity update (ZUPT) uses the known velocity at stationary epoch as a benchmark to calibrate the velocity drift. However, stationary epoch only takes up 24% of a whole gait cycle time, and the velocity drift at the remaining 76% time is usually estimated according to an assumption that velocity has a linear drift over time, which would introduce errors. In this paper, a two-step velocity calibration method was proposed based on human gait characteristics with Smart Insole: known velocity update (KUPT) and double-foot position calibration (DFPC). KUPT could measure the velocity from heel-strike to toe-off based on the recorded real-time foot angle and the shoe dimensions, which increases the time period when the velocity could be measured from 24% to 62% of a whole gait cycle time. DFPC method could fuse the position information of both feet based on the symmetrical characteristic of human gait to further increase the reliability of the localization results. The statistical result of a 20 times 20-m walking experiment showed that KUPT method was more accurate and reliable than ZUPT method for both feet, and DFPC method could further improve the result of KUPT method. Another experiment about walking in an indoor environment for 91 m showed that the proposed KUPT+DFPC method had an error of about 0.78 m which is acceptable for most IoT applications.

Spectral diagnostic system for light impurity transport study in J-TEXT Tokamak

A light impurity diagnostic system is developed for the J-TEXT tokamak. This diagnostic system consists of carbon V (227.09 nm), carbon III (464.7 nm) and edge rotation diagnostics. The carbon V diagnostic consists of a 12-core fiber bundle for light collection, an aberration-corrected monochromator, and a 12-channel photomultiplier tube array. The carbon III diagnostic adopts three identical 18-channel Si photodiode arrays to cover the edge region of the high-field side (HFS), low-field side (LFS) and limiter regions at different toroidal positions, with a specified front filter. The carbon VI (529.26 nm) diagnostic consists of a 10-core fiber bundle, an aberration-corrected monochromator, and an electron-multiplying CCD camera. The system coverage range is 0.2 m to 0.07 m of the HFS. A high-resolution spectroscopic diagnostic can detect carbon III (229.69 nm) and carbon V (227.09 nm) radiation intensities in the LFS. An accurate absolute calibration is carried out by an integrating sphere light source, and a relative position calibration is developed for all diagnoses. Combining the impurity emission profile which derived from inversion and plasma parameter profile, the impurity density of each ion stage and impurity transport coefficients are obtained by a one-dimensional impurity transport code.

Compressed sensing method for measuring absorption spectrum of liquid samples

For low-light or near-infrared absorption spectrum measurements, it is challenging to obtain high resolution spectra due to limitations of exotic array detectors. In this paper, a new spectral measurement method based on compressed sensing (CS) is reported. An experimental spectrometer is constructed and calibrated, and the absorption spectra of two liquid samples are measured. Along with a high resolution, the new method has a better signal-to-noise ratio (SNR) than the conventional scanning spectroscopy technique. The measurement resolution of our experimental system is 0.38 nm. The result of wavelength position calibration is accurate. The peak value of characteristic spectrum of red sample is 730 nm, and that of blue sample are 440 nm and 740 nm.

Handheld target probe tip center position calibration for target-based vision measurement system

The calibration of the handheld target probe tip center position (PTCP) is an essential procedure in a target-based vision measurement system (T-VMS). At present, handheld PTCP calibration methods typically work via the least squares (LS) method, which is easily affected by noise and may generate a sizable error if placed improperly. This paper proposes a regularized total least squares (RTLS) method for handheld target PTCP calibration. Feature points on the handheld target are first subjected to a robust matching strategy, and then positioned precisely by center extraction deviation compensation. Fixed-radius constraint equations derived from the three-dimensional coordinates of feature points are then used to establish an errors in variables (EIV) model of the PTCP. Finally, Tikhonov-regularized and L-curve methods are applied to search for the optimal solution of the EIV model, i.e. the PTCP coordinates. The proposed method was applied in the laboratory and on site to test its accuracy. Practical data demonstrated that it can calibrate the PTCP of a handheld target effectively and with better accuracy.

Research on Automatic Tool Delivery for CNC Workshop of Aircraft Equipment Manufacturing

Aiming at the inefficiency of tool distribution in CNC workshop of aircraft equipment manufacturing, and adapting to the particularity of distribution without large network environment, The solution of intelligent tool delivery using AGV based on machine vision and QR Code navigation is proposed. Image processing of AGV path ribbon, path navigation error analysis and QR Code position calibration are studied in the planned path to achieve machine vision plus QR Code redundant navigation positioning. The AGV can complete the accurate loading and unloading tool of the robot library through the QR Code interaction mode with the machine tool. To realize automatic distribution of tool in CNC workshop of aircraft equipment manufacturing.

Development of a novel cardiopulmonary resuscitation measurement tool using real-time feedback from wearable wireless instrumentation

AimThe design and implementation of a wearable training device to improve cardiopulmonary resuscitation (CPR) is presented. MethodsThe MYO contains both Electromyography (EMG) and Inertial Measurement Unit (IMU) sensors which are used to detect effective CPR, and the four common incorrect hand and arm positions viz. relaxed fingers; hands too low on the sternum; patient too close; or patient too far. The device determines the rate and depth of compressions calculated using a Fourier transform and dual-quaternions respectively. In addition, common positional mistakes are determined using classification algorithms (six machine learning algorithms are considered and tested). Feedback via Graphical User Interface (GUI) and audio is integrated. ResultsThe system is tested by performing CPR on a mannequin and comparing real-time results to theoretical values. Tests show that although the classification algorithm performed well in testing (98%), in real time, it had low accuracy for certain categories (60%), which are attributable to the MYO calibration, sampling rate and misclassification of similar hand positions. Combining these similar incorrect positions into more general categories significantly improves accuracy, and produces the same improved outcome of improved CPR. The rate and depth measures have a general accuracy of 97%. ConclusionThe system allows for portable, real-time feedback for use in training and in the field, and shows promise toward classifying and improving the administration of CPR.

Calibration of position and orientation for point light source synchronously with single image in photometric stereo.

In this paper, a calibration method for non-isotropic point light source is developed, which is capable of calibrating position and orientation of the point light source with a single image synchronously. Based on the bidirectional reflectance distribution function (BRDF), the relationship between the shape of observed surface and the recorded grayscale image is firstly investigated in a more accurate way. Based on this model, a cost function is proposed to evaluate the estimation error, and a new cumulative, error-free iteration method is designed to recursively estimate the point light source parameters. The average simulation rebuilding root mean square error (RMSE) is below 0.9. The experiments are performed by calibrating a point light source in a photometric stereo measurement system, and the corresponding RMSE is below 1.2 in the unit of grayscale. Further analysis shows one image is enough to achieve the precision calibration using our proposed method.

Position and orientation calibration of a 2D laser line sensor using closed-form least-squares solution

Abstract Laser line sensors are used for inspecting, positioning and scanning 3D objects. They are often mounted on the flange of an industrial robot. The laser line sensor provides 2D measurement values, in the x and z direction with respect to the sensor coordinate frame. In order to transform the measured values into the robot coordinate frame and therefore expand the 2D measured values into 3D coordinates, the position and orientation of the sensor coordinate frame with respect to the flange coordinate system must be determined by solving a kinematic equation in terms of transformation matrices. This article provides a complete solution for solving this problem. A unique solution is derived based on the separable closed-form solution after two movements of the robot flange under satisfying constraints [Shiu & Ahmad (2014)]. Robotic applications are usually implemented with the presence of noise. Therefore, a least-squares solution is determined after performing several measurements [Park & Martin (1994)].

基于共面约束的多线激光雷达相对位置关系检校

基于共面约束的多线激光雷达相对位置关系检校

SoundMark: Accurate Indoor Localization via Peer-Assisted Dead Reckoning

Pedestrian dead reckoning enables pervasive indoor localization without a site survey on fingerprints or an intensive deployment of infrastructures. But accumulated errors in dead reckoning limit the spread of pervasive indoor location-based services. Existing landmark-based approaches mostly rely on resetting the user’s position with the landmark position only when the user is detected while on arrival at a landmark. However, such methods are still restricted by the specific movement patterns and sparse landmark distributions so that the opportunity for position calibration is limited. In this paper, an accurate peer-assisted localization system (called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SoundMark</i> ) on a smartphone with no prior infrastructure or fingerprinting is proposed. It calibrates mobile user’s dead reckoning position by leveraging the location constraints between another stationary user who arrives at a landmark. To detect whether a user arrives at a landmark, motion pattern is extracted by fusing the multiple sensors. Then, user activity in the landmark is decomposed to determine whether the user is stationary for performing audio ranging. Besides, SoundMark also applies a mobility-induced time-difference-of-arrival-based audio ranging to extract the location constraints between the peers for localization. SoundMark is implemented on the Android platform for evaluations. The results show that the accuracy of proposed peer-assisted localization is within 2.1 m at the percentage of 80%.

Risk analysis of electronic intraoperative radiation therapy for breast cancer

PurposeTo evaluate the process and improve safety of intraoperative radiation therapy (IORT) for early-stage breast cancers treated with electronic brachytherapy. Methods and MaterialsA multidisciplinary team conducted a failure mode and effects analysis (FMEA) for IORT breast cancer treatments by first developing a process map. This map was then used to identify failure modes for all steps in the treatment workflow. Risk priority numbers (RPNs) were assigned to each failure mode and were calculated as the product of the failure mode's probability of occurrence (O), severity (S), and lack of detectability (D). Corrective steps were implemented to address failure modes with the highest risk, and a revised process was generated. ResultsThe steps with the highest risk failure modes were related to source calibration, use of correct plan and dwell times, and the correct site and intent. The introduction of a physician calibration check and an extended time-out checklist reduced the risk of these failure modes. The highest risk steps in the Xoft breast IORT treatment process are associated with source calibration and manual entry of dwell positions for each balloon size and volume combination. High-risk failure modes that could be mitigated with improved hardware and software interlocks were identified. ConclusionHigh-risk failure modes are identified with FMEA and addressed with corrective steps. This application of FMEA can be used in principle for clinical processes throughout breast cancer care. This analysis demonstrates the importance of well-designed QC policies, procedures, and oversight in a Xoft electronic brachytherapy program for breast cancer IORT.

Design and Characterization of a Scintillator-Based Position-Sensitive Detector for Muon Imaging

This work presents the design of a position-sensitive detector that we are evaluating for cosmic-ray muon imaging. The position-sensitive detector consists of an EJ-200 plastic scintillator panel that is 32 × 32 × 2.5 cm in dimension. A quantity of 32 parallel grooves, each 2 mm wide and 4 mm deep with a pitch of 1 cm, are carved on the top and bottom sides, in perpendicular orientation, of a scintillator panel. Two wavelength shifting optical fibers are embedded in each groove for light collection and transport. The optical fibers from each channel are coupled to one pixel of a Hamamatsu H8500C multi-anode photomultiplier tube. An encoding technique using a one-dimensional resistor network was developed to reduce the number of required readout channels for position determination. The position calibration was performed with a blue light emitting diode. The detector was shown to achieve position resolution of ~1 cm (sigma).

Sound Source Omnidirectional Positioning Calibration Method Based on Microphone Observation Angle

To get source azimuth from microphone observation angle of view in a complex real environment, this article, on the basis of the analysis of geometric positioning method, established a seven-element microphone array model and proposed a sound source omnidirectional positioning calibration method based on microphone observation angle. By using a seven-element array to invert the position and angle of a sound source, the relative time delay value of a pair of microphones on the vertical axis of the coordinate system is used to determine the elevation angle polarity and realize the omnidirectional sound source positioning. The array parameters, sound velocity, array size, horizontal deflection angle, elevation angle, and sound source are analyzed, and the error method is proposed. The sound source data was measured using the microphone array perspective, and a new Cartesian coordinate system was established based on the observation angle of view for omnidirectional positioning calibration of the sound source. The simulation results show that the position error of the method is about 0.01% and the angle error is about 0.005%, with high calibration accuracy. The actual measurement results show that this method can effectively calibrate the sound source azimuth, the error rate of the source coordinates is around 10%, the horizontal declination angle error is less than 5%, and the elevation angle error is less than 8%. Appropriately increasing the spacing of the array will have a better calibration effect in an actual complex experimental environment.

On-line calibration and uncertainties evaluation of spherical joint positions on large aircraft component for zero-clearance posture alignment

Abstract With the improvement of performance requirements for modern aircraft, such as speed and leak tightness, the posture alignment of large components without clearance is now extremely required in the aircraft industry. Nevertheless, the inherent errors of both the components themselves and the posture alignment system lead to high risk of collision during the inserting stage, among which the positional errors of spherical joints that connecting the large component to the numerical controlled locators are identified as the primary error source by existing studies. In this paper, a novel method for on-line correction and uncertainties evaluation of the positions of spherical joint centers (SJCs) is presented. Firstly, the rough positions of SJCs are identified based on the nominal model, and the finite element analysis (FEA) method is applied to preliminarily compensate the self-weight deformation of the component. Secondly, the on-line correction model of SJCs is further established, majorly on the basis of the displacements of locators and the relative postures between the initial posture and the new posture after each motion. Thirdly, to improve the correction accuracy, a new relative posture evaluation model considering the anisotropic measurement uncertainties of key points is suggested and solved by particle swarm optimization, and the correction uncertainties are then analyzed using Monte Carlo simulation. According to the numerical experiments, the proposed relative posture evaluation method has demonstrated more robustness evaluation results than the conventional approaches, and also leads to lower correction uncertainties of SJCs. Moreover, since the relative posture evaluation is a common problem in robot calibration, it also provides a promising alternative or supplement for the conventional optimal posture selection method to improve calibration accuracy. The practical application for a wing to fuselage assembly has verified the effectiveness of the correction method, in which the largest positional error of SJCs has decreased from about 14.2 mm to less than 0.4 mm after correction, and the displacement calculation error has been accordingly reduced from 0.1 mm to smaller than 0.01 mm. Therefore, the security of posture adjustment in confined clearance has been largely enhanced.

Separating eccentricity deviation in transfer torque wrench calibrations

An approximation method is proposed to achieve the contribution of the square drive eccentricity in transfer torque wrench calibrations. This systematic contribution can thus be quantified and eliminated. By doing this, the influence of the contact surfaces in the square drive can be estimated more precisely. The approximation succeeds not only at complete 4- position calibrations but also – with the help of a numerical fit – with calibrations over only 3 positions, a procedure which is required in the current German guideline for torque wrench calibrations. The proposed method has been validated through a survey of transfer torque wrench calibrations and through Monte Carlo simulations.

Error analysis of applicator position for combined internal/external radiation therapy in cervical cancer.

The aim of this study was to analyze the error variation in the applicator placement during the first and second radiotherapy session for cervical cancer. We recruited 22 patients with cervical cancer treated with radiotherapy. According to the image output in the first and second CT-Sim inspection, we conducted comparative analysis of image fusion to accurately measure the errors in applicator position in the horizontal (X-), longitudinal (Y-) and vertical (Z)-axes. The calibration processing was implemented in accordance with the data error measured and the location parameters, such as the angle and depth of the applicator. Electronic portal imaging technology (EPID) was used to calibrate posture change amplitude for the extracorporeal irradiation of patients, and dynamic measurement with applicator position was used to describe the error of the parameters. Finally, the data from two measurements in CT-Sim, digital reconstruction radiography (DRR) and EPID were compared. After calibration, the mean value of error of the applicator were significantly smaller. Image registration planning for error parameter calibration of applicator position can effectively reduce the applied horizontal spatial position error in radiotherapy treatment, and improve the accuracy and effectiveness during treatment.

Air Defense Position Calibration Process Based on Improved Particle Swarm Optimization

In order to improve the efficiency of calibration, aiming at the shortcomings of traditional relative calibration method of a certain air defense weapon system position, an optimization method based on intelligent algorithm for the relative calibration process of vehicle in a position is proposed. In this paper, the basic process of vehicle calibration is briefly introduced. The mathematical model of calibration process is established to optimize the total calibration time. The method for solving the calibration process using discrete binary particle swarm optimization is given. Through a simulation example of a vehicle calibration problem, after comparing the optimization results of discrete binary particle swarm optimization and genetic algorithm, it shows that discrete binary particle swarm has better application value in this problem. The research shows that the discrete binary particle swarm can effectively improve the calibration efficiency.