Distance Measurement Error Research Articles

A stepwise parameter identification strategy for probe-based robot on-machine measurement system calibration based on sensitivity analysis

The probe-based measurement presents an economical and efficient on-machine measurement (OMM) method. However, the low position accuracy of robot presents significant challenges for probe-based robot OMM. To improve the measurement accuracy of robot OMM system, this paper calibrates the geometric parameters of robot OMM system through a closed-loop calibration method with sphere constraint. First, the geometric error model for robot OMM system is established. Given the difficulty in model parameter identification, this paper defines a new index, the relative distance sensitivity index (RDSI), to reveal the contribution of model parameter to relative distance accuracy. Subsequently, sensitivity analysis is conducted on model parameters based on RDSI and model parameters are grouped according to the analysis results. In parameter identification, parameters are identified step by step according to the grouping results. Experiment results show that after calibration, the max distance measurement error of robot OMM system is reduced from 0.54 mm to 0.12 mm.

An error compensation method for on-machine measuring blade with industrial robot

To achieve the seamless integration of precision grinding blade with timely measured data, an on-machine measurement system employing industrial robot is developed. The limitation to its widespread application lies in the accuracy of measurement, prompting the proposal of an error compensation method to address the measurement error within the implemented blade on-machine measurement system. To address the pre-travel error in the measuring device of the on-machine measurement system, an analysis of the factors influencing the pre-travel error of the contact probe is conducted. Subsequently, pre-travel error data is gathered utilizing the experimental calibration method involving a standard ball, and a prediction model employing the bilinear interpolation algorithm is established to facilitate error compensation. Employing pre-travel error compensation for the analysis of the operating body error in the on-machine measurement system, a spherical center distance constraint error model is derived through closed-loop kinematic calibration of the six-degrees-of-freedom industrial robot. Kinematic parameter error identification is conducted using a hybrid algorithm combining the L-M algorithm and the adaptive factor double-variable DE algorithm. This approach diminishes the spherical center distance measurement error, reducing it from 0.081 mm to 0.016 mm. Subsequently, experiment is conducted to measure blade machining allowances using an on-machine robotic measurement system, comparing the obtained data with measurement from a blue light scanner and a coordinate measuring machine (CMM). The results reveal average absolute deviations of 0.020 mm, 0.015 mm, and 0.016 mm in the three blade cross sections for the on-machine robotic measurement system and the blue light scanner, respectively. Correspondingly, the average absolute deviations for the on-machine robotic measurement system and the CMM in the three blade sections are 0.028 mm, 0.029 mm, and 0.029 mm. Moreover, the on-machine measurement system demonstrates commendable measurement repeatability, with a standard deviation of 0.003 mm.

Research on SLAM Localization Algorithm for Orchard Dynamic Vision Based on YOLOD-SLAM2

With the development of agriculture, the complexity and dynamism of orchard environments pose challenges to the perception and positioning of inter-row environments for agricultural vehicles. This paper proposes a method for extracting navigation lines and measuring pedestrian obstacles. The improved YOLOv5 algorithm is used to detect tree trunks between left and right rows in orchards. The experimental results show that the average angle deviation of the extracted navigation lines was less than 5 degrees, verifying its accuracy. Due to the variable posture of pedestrians and ineffective camera depth, a distance measurement algorithm based on a four-zone depth comparison is proposed for pedestrian obstacle distance measurement. Experimental results showed that within a range of 6 m, the average relative error of distance measurement did not exceed 1%, and within a range of 9 m, the maximum relative error was 2.03%. The average distance measurement time was 30 ms, which could accurately and quickly achieve pedestrian distance measurement in orchard environments. On the publicly available TUM RGB-D dynamic dataset, YOLOD-SLAM2 significantly reduced the RMSE index of absolute trajectory error compared to the ORB-SLAM2 algorithm, which was less than 0.05 m/s. In actual orchard environments, YOLOD-SLAM2 had a higher degree of agreement between the estimated trajectory and the true trajectory when the vehicle was traveling in straight and circular directions. The RMSE index of the absolute trajectory error was less than 0.03 m/s, and the average tracking time was 47 ms, indicating that the YOLOD-SLAM2 algorithm proposed in this paper could meet the accuracy and real-time requirements of agricultural vehicle positioning in orchard environments.

Spatial distortions in swept source optical coherence tomography due to lateral scanning

The paper presents errors in axial distance measurements and deviations of contours in swept source (SS) optical coherence tomography (OCT) cross sections due to lateral scanning. The study shows how these errors and deviations depend on the adjustments of the interface optics between a lateral scanner device and the target imaged. A theoretical model and experiments demonstrate that these errors and deviations are given by the Doppler shift frequency imprinted by the lateral scanning. The smaller the number of sweeps per lateral scanning interval, the larger these errors and deviations. The study also shows that the sign of error and deviation of contours can be put in correspondence with the spectral sweeping direction. Even more, it is shown that such effects can be used to predict the tuning direction of the swept source without an optical spectrum analyzer.

A Reappraisal of the Accuracy of the Tactile Method for the Detection of the Subgingival Cementoenamel Junction: An In Vivo Study.

This article reappraises the accuracy and factors associated with the detection of the cementoenamel junction (CEJ) using the tactile method. A total of 111 tooth sites of 7 patients scheduled for flap surgery were selected for the study. The CEJ was detected in a blind manner using the conventional tactile method with a standard periodontal probe by a single, trained examiner. A custom-made stent was prepared to standardize the measurements and the distance from a fixed reference point on the stent to the CEJ was measured before (apparent CEJ) and after (real CEJ) opening a gingival flap. To evaluate the effect of local anesthesia (LA) on the measurement error, assessment with and without LA given prior to the measurement was also evaluated. The bone crest-CEJ distance at each site was also recorded in all sites. The measurement error of apparent versus real distance, if any, was compared using Cohen's weighted kappa coefficient (WKC) (± 1 mm). A weak WKC (WKC = 0.539) was found between the apparent and real CEJ distance. Higher WKCs were noted at posterior and proximal sites than the anterior and buccal/lingual sites, respectively (0.840 and 0.545 vs. 0.475 and 0.488). A higher confluence of the agreements was noted when CEJ distance was measured in anesthetized sites (WKC = 0.703). Sites without bone loss showed more coronal deviation of CEJ detection, as opposed to apical deviation seen at sites with bone loss. The conventional CEJ detection using the tactile method was relatively imprecise depending on the anatomical location of the tooth and the bone loss at the site of measurement. However, the detection accuracy improved when the sites were anesthetized. In clinical terms, our data, reported here for the first time imply that, in the absence of visual cues, posterior tooth site measurements of periodontal attachment loss were more reliable in comparison to the other sites. The bone crest level also impacted the measurement deviation to some extent, implying that, possible overestimate of clinical attachment loss may occur at sites without bone loss.

A Combined Filtering Method for ZigBee Indoor Distance Measurement.

Indoor distance measurement technology utilizing Zigbee's Received Signal Strength Indication (RSSI) offers cost-effective and energy-efficient advantages, making it widely adopted for indoor distance measurement applications. However, challenges such as multipath effects, signal attenuation, and signal blockage often degrade the accuracy of distance measurements. Addressing these issues, this study proposes a combined filtering approach integrating Kalman filtering, Dixon's Q-test, Gaussian filtering, and mean filtering. Initially, the method evaluates Zigbee's transmission power, channel, and other parameters, analyzing their impact on RSSI values. Subsequently, it fits a signal propagation loss model based on actual measured data to understand the filtering algorithm's effect on distance measurement error. Experimental results demonstrate that the proposed method effectively improves the conversion relationship between RSSI and distance. The average distance measurement error, approximately 0.46 m, substantially outperforms errors derived from raw RSSI data. Consequently, this method offers enhanced distance measurement accuracy, making it particularly suitable for indoor positioning applications.

LSTM-DL: A Counting Optimization Approach for LSTM-Based DV-Hop Localization Model in Wireless Sensor Networks

The quest for precise localization of unknown nodes in Wireless Sensor Networks (WSN) garners significant academic attention, further intensified by the burgeoning domain of meta-heuristic algorithms. Traditional localization methods, such as the Least Squares Method (LSM), inherently yield lower accuracy, a limitation that this paper aims to transcend. We introduce a robust deep learning model grounded in Long Short-Term Memory (LSTM-DL) designed to enhance localization processes by effectively minimizing distance measurement errors in network topologies. This approach is augmented with an improved evaluation function, meticulously tailored to mitigate topological inaccuracies. Through rigorous experimental validation, the LSTM-DL model demonstrates a remarkable performance leap, surpassing the conventional DV-Hop method and outperforming existing meta-heuristic algorithms in accuracy and reliability. The findings decisively suggest that meta-heuristic approaches, and specifically the advanced LSTM-DL, hold substantial promise over traditional DV-Hop in the sphere of node localization within WSNs.

Calibration method for binocular vision system with large field of view based on small target image splicing

In vision measurement, camera calibration has a significant impact on measurement precision. The classical target-based calibration methods require the target to occupy more than one-third of the field of view. A small-size target that does not meet the requirements results in poor calibration accuracy, while an appropriate large-size target is difficult to manufacture and inconvenient to operate. In view of the above problem, we propose a flexible and accurate calibration method based on small target image splicing to calibrate the binocular vision system with a large field of view. The spliced images and virtual large targets are constructed to extend the target size, providing better flexibility for calibration. Moreover, an optimization objective function integrating two constraints in the imaging plane and measurement space is presented to improve the calibration accuracy during the parameter optimization process. The simulation experiments and actual experiments are carried out to test the performance of the proposed method. The results demonstrate that the calibration accuracy of the proposed method using a small target is equivalent to that of Zhang’s method using a large target. Additionally, when using a same-size target, the parameter error of the proposed method is less than that of Zhang’s method, and the proposed method reduces the distance measurement error from 1.169 mm to 0.208 mm compared to Zhang’s method.

Fault distance measurement method for wind power transmission lines based on improved NSGA II

A fault distance measurement method that is suitable for long-distance wind power transmission lines is proposed by this paper. By combining the voltage and current at both ends of the line during normal operation, a dynamic line parameter correction method based on improved NSGA II is proposed to ensure measurement errors caused by parameter changes are avoided. Based on the construction of the fault distance measurement function, a global optimization method that is based on adaptive golden section search is proposed, where only the power frequency measurement data at both ends of the bus is required and synchronization is not required for the measurement of fault distance. A large number of experimental results demonstrate that the method this paper proposes is highly adaptable, with a relative distance measurement error of less than 0.2 km, and high accuracy is maintained in distance measurement even with certain degrees of noise interference.

Robust Positioning Estimation for Underwater Acoustics Targets with Use of Multi-Particle Swarm Optimization

With the extensive application of sensor technology in scientific ocean research, ocean resource exploration, underwater engineering construction, and other fields, underwater target positioning technology has become an important support for the ocean field. This paper proposes a robust positioning algorithm that combines the disadvantages of distributed estimation and particle swarm optimization, which can solve the large localization error problem caused by uncertainties in underwater acoustic communication and sampling processes. Considering the presence of ranging anomalies and sampling packet loss in underwater acoustic measurements, a weighted coupling filling method is used to correct the outliers in an underwater acoustic ranging signal. Based on the mapping model from the element array to the underwater acoustic responder, an unconstrained optimization algorithm for one-time localization estimation of underwater acoustic targets was established. Based on the one-time localization estimation results of underwater acoustic targets, an improved multi-particle swarm optimization estimation based on interactive search is proposed, which improves the accuracy of underwater target localization. The numerical results show that the positioning accuracy of the proposed algorithm can be effectively enhanced in cases of distance measurement errors and azimuth measurement errors. Compared with the positioning error before optimization, the positioning error can be reduced after optimization. Additionally, the experiment was carried out in the underwater environment of Hangzhou Qiandao Lake, which verified the positioning performance of the proposed algorithm.

Measuring Received Signal Strength of UWB Chaotic Radio Pulses for Ranging and Positioning

The use of ultra-wideband (UWB) signals for local positioning is very attractive for practice, because such signals have the potential to provide centimeter precision. In this paper, we consider wireless ranging (distance measurement) and positioning, using one of the kinds of UWB signals, i.e., chaotic radio pulses, which are noise-like signals with no constant shape. The distance measurement is based on an assessment in the receiver of the power of UWB chaotic radio pulses emitted by the transmitter. A new method for estimating their power and its experimental implementation is proposed and described. Experimental layouts of the transmitter and receiver and the principles of their operation are described. To determine the main features of this method under real signal propagation conditions, full-scale indoor measurements were carried out, and statistical estimates of the accuracy were made. We present the results of experimental testing of the proposed approach for positioning the emitter relative to a system of anchors in an office space 6 × 6.5 m2 in the mode of measuring object coordinates on a line and on a plane. The mean absolute error (MAE) of distance measurement (1D) was 25 cm, and the root mean squared error (RMSE) was 39 cm. When positioning on a plane (2D), the MAE of coordinate estimation was 34 cm and the RMSE was 42 cm. The proposed distance measurement method is intended for use in wireless UWB transceivers used in wireless sensor networks.

Deep focus light-field camera for handheld 3D intraoral scanning using crosstalk-free solid immersion microlens arrays.

3D in vivo imaging techniques facilitate disease tracking and treatment, but bulky configurations and motion artifacts limit practical clinical applications. Compact light-field cameras with microlens arrays offer a feasible option for rapid volumetric imaging, yet their utilization in clinical practice necessitates an increased depth-of-field for handheld operation. Here, we report deep focus light-field camera (DF-LFC) with crosstalk-free solid immersion microlens arrays (siMLAs), allowing large depth-of-field and high-resolution imaging for handheld 3D intraoral scanning. The siMLAs consist of thin PDMS-coated microlens arrays and a metal-insulator-metal absorber to extend the focal length with low optical crosstalk and specular reflection. The experimental results show that the immersion of MLAs in PDMS increases the focal length by a factor of 2.7 and the transmittance by 5.6%-27%. Unlike conventional MLAs, the siMLAs exhibit exceptionally high f-numbers up to f/6, resulting in a large depth-of-field for light-field imaging. The siMLAs were fully integrated into an intraoral scanner to reconstruct a 3D dental phantom with a distance measurement error of 82 ± 41 μm during handheld operation. The DF-LFC offers a new direction not only for digital dental impressions with high accuracy, simplified workflow, reduced waste, and digital compatibility but also for assorted clinical endoscopy and microscopy.

Phase-Locked Synthetic Wavelength Interferometer Using a Femtosecond Laser for Absolute Distance Measurement without Cyclic Error.

We present a phase-locked synthetic wavelength interferometer that enables a complete elimination of cyclic errors in absolute distance measurements. With this method, the phase difference between the reference and measurement paths is fed back into a phase lock-in system, which is then used to control the synthetic wavelength and set the phase difference to zero using an external cavity acousto-optic modulator. We validated the cyclic error removal of the proposed phase-locked method by comparing it with the conventional phase-measuring method of the synthetic wavelength interferometer. By analyzing the locked error signal, we achieved a precision of 0.6 mrad in phase without any observed cyclic errors.

Temperature influence on optical fiber and temperature compensation method for a frequency modulation continuous wave absolute distance measurement system.

A temperature compensation method is proposed to solve the ranging precision decrease problem of the frequency-modulated continuous wave distance measurement system. The set of phases spread frequency sampling method is used to correct the beat frequency signal non-linearity. The influence model of temperature on the optical fiber auxiliary interferometer is studied. The experimental results show that distance measurement error decreases from 0.3432 mm to 0.02260 mm, and the mean measurement standard deviation decreases from 0.1088 mm to 0.01733 mm on a maximum measurement range of 1.6 m after compensation.

Application of photogrammetric methods for locating and tracking cetacean movements at sea

Accurate measurements of the locations of surfacing cetaceans are important data for behavioural studies and sightings surveys. A system for tracking cetacean movements based on photogrammetric analysis of digital images has been developed and tested at sea. Radial distances from the ship to surfacing whales were calculated from video images by measuring the angle of dip between the whale and the horizon. Bearings were either measured from still images of reference points on the ship, from a magnetic bearing compass or from the bearing ring of stand-mounted binoculars. The system uses readily available equipment and can be operated by one person. Calibration tests were conducted to assess the accuracy of the system. Errors in distance measurement increased approximately linearly with distance. Under typical survey conditions, from a large vessel with an eye height of 18m, distances to whales could be measured with a root mean square error of 3.5%. A model was developed to enable corrections to be made for atmospheric refraction. This has implications for other studies using reticle binoculars. If refraction is not corrected then distance estimates will be negatively biased. Field trials of the system were conducted from several different types and sizes of vessel during studies of a number of different species. Results of these trials demonstrated that the system is a practical tool for fine-scale tracking of cetacean movements and could also be used on line transect surveys. The limitations of the system are the need for a clear horizon and difficulties, for some species, in obtaining suitable quality images of all surfacings. There is also a moderate overhead in increased analysis time. Advances in digital imaging technology are likely to solve many of the image quality problems in the future.

A Novel Semidefinite Programming-based UAV 3D Localization Algorithm with Gray Wolf Optimization

The unmanned aerial vehicle (UAV) network has gained vigorous evolution in recent decades by virtue of its advanced nature, and UAV-based localization techniques have been extensively applied in a variety of fields. In most applications, the data captured by a UAV are only useful when associated with its geographic position. Efficient and low-cost positioning is of great significance for the development of UAV-aided technology. In this paper, we investigate an effective three-dimensional (3D) localization approach for multiple UAVs and propose a flipping ambiguity avoidance optimization algorithm. Specifically, beacon UAVs take charge of gaining global coordinates and collecting distance measurements from GPS-denied UAVs. We adopt a semidefinite programming (SDP)-based approach to estimate the global position of the target UAVs. Furthermore, when high noise interference causes missing distance pairs and measurement errors, an improved gray wolf optimization (I-GWO) algorithm is utilized to improve the positioning accuracy. Simulation results show that the proposed approach is superior to a number of alternative approaches.

Assessment of jugular bulb variability based on 3D surface models: quantitative measurements and surgical implications

PurposeHigh-riding jugular bulbs (JBs) among other anatomical variations can limit surgical access during lateral skull base surgery or middle ear surgery and must be carefully assessed preoperatively. We reconstruct 3D surface models to evaluate recent JB classification systems and assess the variability in the JB and surrounding structures.Methods3D surface models were reconstructed from 46 temporal bones from computed tomography scans. Two independent raters visually assessed the height of the JB in the 3D models. Distances between the round window and the JB dome were measured to evaluate the spacing of this area. Additional distances between landmarks on surrounding structures were measured and statistically analyzed to describe the anatomical variability between and within subjects.ResultsThe visual classification revealed that 30% of the specimens had no JB, 63% a low JB, and 7% a high-riding JB. The measured mean distance from the round window to the jugular bulb ranges between 3.22 ± 0.97 mm and 10.34 ± 1.41 mm. The distance measurement (error rate 5%) was more accurate than the visual classification (error rate 15%). The variability of the JB was higher than for the surrounding structures. No systematic laterality was found for any structure.ConclusionQualitative analysis in 3D models can contribute to a better spatial orientation in the lateral skull base and, thereby, have important implications during planning of middle ear and lateral skull base surgery.

Vision measuring technology for the position degree of a hole group.

The hole is one of the most important geometric elements in mechanical parts. The center distance of a hole group measurement method based on machine vision is proposed for solving the influence of perspective distortion and improving the applicability of vision systems. In the method, the plane equation of the measured plane is obtained by the line structured light vision technology, and the process is free from the constraints of the calibration plate. In order to eliminate the effect of projection distortion on the measurement accuracy, a local coordinate system is established on the plane of the measured hole group, the hole diameter, and the center distance of the hole group, which could be calculated by the local coordinates of the hole edge points. In the experiment, the flange is taken as the measured object, the distances between the holes on the flange are obtained by the method proposed in this paper, and the measurement results compared with the data are obtained by a coordinate measuring machine (CMM). The experimental results show that the average measurement error of center distance is 0.0739mm, and the standard deviation is 0.0489mm.

Photonics-assisted simultaneous detection of distances and directions for multi-targets based on polarization multiplexing and spectrum symmetry

A photonics-assisted simultaneous detection method of distances and directions for multiple targets is proposed based on polarization multiplexing and spectrum symmetry. A linear frequency modulation transmitting signal is generated by photonic frequency doubling. The echo signals are received by a three-antenna based linear array. The intermediate antenna supplies overlapped reference spectra by orthogonal modulation. According to specific spectrum symmetry, the de-chirped frequencies of echo signals from each target are clearly distinguished through polarization demultiplexing. Thus, distances and directions can be decoupled for multi-targets without direction ambiguity. Three-target proof-of-concept experiments have verified that the average measurement errors of distance and direction are 3.7 cm and 0.39°. The direction measurement range is up to 166.78°. A multi-target detection scheme with a large direction range is provided for the complex electromagnetic environment.

Estimation of harvested fruit weight using volume measurements with distance sensors: A case study with olives in a big box

The introduction of fruit tree harvesters on the market allows the opportunity to incorporate new yield monitors. Traditionally, yield has been measured by in-the-field fruit batch weighing systems that employ load cells, which present certain problems as well as oscillations and outliers. We propose the development and evaluation of two distance measurement systems (an experimental one using an array of sensors with low-cost, Time-of-Flight technology and another, commercial system, with a 3D camera) to estimate the volume of fruit harvested in a big box and correlate the volume with its weight. To this end, two algorithms were developed to estimate the volume of fruit filling. Several tests were conducted to determine the field of view of the sensors and the influence of illumination, reflectivity of different surfaces, and vibrations in transit on the measurements they give. Illumination was a limiting factor on the accuracy of the experimental system and required mitigating actions to operate with it. The mean relative error of sensor distance measurement was less than 0.8 % and 1.6 % for the commercial and experimental systems, respectively, which decreased as distance from the measurement target increased. Measurements on matte surfaces showed a lower measurement error than those on glossy surfaces, with error being twice as high in the commercial system than in the experimental system. The error in volume estimation was lower in the commercial system and could be reduced to less than 1.6 % with pre-calibration. In general, with the accelerations typical of agricultural traffic, in dynamic operation the distance sensors provided less variation in results than the load cells, which would require processing of the recorded signals. In the range of filling a box over 150 kg, the absolute error in weight estimation was 5.4 kg for the experimental system and 11.0 kg for the commercial system. However, this error may increase with the use of the experimental system if filling occurs from the center or from the corner. In general, the systems offer acceptable results for using this technology if extreme accuracy is not required. This work establishes the basics of a technology that can be an alternative to load cells and be applied to harvesting machinery to record continuous real-time production.