Search

In this paper, we present a laser triangulation sensor to measure the distance between the sensor and an object without contact using a diffraction slit rather than a traditional lens. We show that by replacing the lens with a slit, we can exploit the resulting diffraction pattern to have finer and yet simpler image analysis, yielding better estimation of the distance to the object. To test our hypothesis, we build a precision position table and a laser triangulation sensor, generate large data sets to test different estimation algorithms on various materials, and compare data acquisition using a traditional lens versus using a slit. We show that position estimation when using a slit is both more precise and more accurate than comparable methods using a lens. [ABSTRACT FROM AUTHOR]

The variety of equipment implementing laser triangulation technology for 3D scanning makes it difficult to analyse their performance, comparability, and traceability. In this study, three laser triangulation sensors arranged in different configurations are analysed using high precision spheres made of different materials and surface finishes. Three types of reference parameters were used: diameter, form error, and standard deviation of the point cloud. The experimentation was based on studying the quality of the point clouds generated by the three sensors, which enabled us to find and quantify an edge effect in the horizon of the scanned surface. A procedure to reach the optimal filtering conditions was proposed, and a chart of recommended usage of each sphere (material and finish) was created for the different types of sensors. This filter enables removal of both spurious points and those few points that spoil the form error, greatly improving the quality of the measurement. [ABSTRACT FROM AUTHOR]

One of the important issues being explored in Industry 4.0 is collaborative mobile robots. This collaboration requires precise navigation systems, especially indoor navigation systems where GNSS (Global Navigation Satellite System) cannot be used. To enable the precise localization of robots, different variations of navigation systems are being developed, mainly based on trilateration and triangulation methods. Triangulation systems are distinguished by the fact that they allow for the precise determination of an object's orientation, which is important for mobile robots. An important feature of positioning systems is the frequency of position updates based on measurements. For most systems, it is 10–20 Hz. In our work, we propose a high-speed 50 Hz positioning system based on the triangulation method with infrared transmitters and receivers. In addition, our system is completely static, i.e., it has no moving/rotating measurement sensors, which makes it more resistant to disturbances (caused by vibrations, wear and tear of components, etc.). In this paper, we describe the principle of the system as well as its design. Finally, we present tests of the built system, which show a beacon bearing accuracy of Δ φ = 0.51 ° , which corresponds to a positioning accuracy of Δ R = 6.55 cm, with a position update frequency of f u p d a t e = 50 Hz. [ABSTRACT FROM AUTHOR]

As incrementally formed sheets show large geometric deviations resulting from the deflection of the forming tool, an in-process measurement of the tool tip position is required. In order to cover a measuring volume of 2.0 m × 1.0 m × 0.2 m and to achieve measuring uncertainties of less than 50 µm, a multi-sensor system based on triangulation is realized. Each shadow imaging sensor in the multi-sensor system evaluates the direction vector to an LED attached to the tool, and the three-dimensional position of the LED is then determined from the combination of two sensors. Experimental results show that the angle of view from the sensor to the LED limits both the measurement range and the measurement uncertainty. The measurement uncertainty is dominated by systematic deviations, but these can be compensated, so that the measurement uncertainty required for measuring the tool tip position in the ISF is achieved. [ABSTRACT FROM AUTHOR]

Distance estimation is one of the oldest and most challenging tasks in computer vision using only a monocular camera. This can be challenging owing to the presence of occlusions, noise, and variations in the lighting, texture, and shape of objects. Additionally, the motion of the camera and objects in the scene can affect the accuracy of the distance estimation. Various techniques have been proposed to overcome these challenges, including stereo matching, structured light, depth from focus, depth from defocus, depth from motion, and time of flight. The addition of information from a high-resolution 3D view of the surroundings simplifies the distance calculation. This paper describes a novel distance estimation method that operates with converted point cloud data. The proposed method is a reliable map-based bird's eye view (BEV) that calculates the distance to the detected objects. Using the help of the Euler-region proposal network (E-RPN) model, a LiDAR-to-image-based method for metric distance estimation with 3D bounding box projections onto the image was proposed. We demonstrate that despite the general difficulty of the BEV representation in understanding features related to the height coordinate, it is possible to extract all parameters characterizing the bounding boxes of the objects, including their height and elevation. Finally, we applied the triangulation method to calculate the accurate distance to the objects and statistically proved that our methodology is one of the best in terms of accuracy and robustness. [ABSTRACT FROM AUTHOR]

In an era of high penetration of renewable energy, accurate photovoltaic (PV) power forecasting is crucial for balancing and scheduling power systems. However, PV power output has uncertainty since it depends on stochastic weather conditions. In this paper, we propose a novel short-term PV forecasting technique using Delaunay triangulation, of which the vertices are three weather stations that enclose a target PV site. By leveraging a Transformer encoder and gated recurrent unit (GRU), the proposed TransGRU model is robust against weather forecast error as it learns feature representation from weather data. We construct a framework based on Delaunay triangulation and TransGRU and verify that the proposed framework shows a 7–15% improvement compared to other state-of-the-art methods in terms of the normalized mean absolute error. Moreover, we investigate the effect of PV aggregation for virtual power plants where errors can be compensated across PV sites. Our framework demonstrates 41–60% improvement when PV sites are aggregated and achieves as low as 3–4% of forecasting error on average. [ABSTRACT FROM AUTHOR]

Many authors have been working on approaches that can be applied to social robots to allow a more realistic/comfortable relationship between humans and robots in the same space. This paper proposes a new navigation strategy for social environments by recognizing and considering the social conventions of people and groups. To achieve that, we proposed the application of Delaunay triangulation for connecting people as vertices of a triangle network. Then, we defined a complete asymmetric Gaussian function (for individuals and groups) to decide zones where the robot must avoid passing. Furthermore, a feature generalization scheme called socialization feature was proposed to incorporate perception information that can be used to change the variance of the Gaussian function. Simulation results have been presented to demonstrate that the proposed approach can modify the path according to the perception of the robot compared to a standard A* algorithm. [ABSTRACT FROM AUTHOR]

Composite material structures are commonly used in many industrial sectors (aerospace, automotive, transportation), and can operate in harsh environments where impacts with other parts or debris may cause critical safety and functionality issues. This work presents a method for improving the accuracy of impact position determination using acoustic source triangulation schemes based on the data collected by piezoelectric sensors attached to the structure. A novel approach is used to estimate the Differential Time-of-Arrival (DToA) between the impact response signals collected by a triplet of sensors, overcoming the limitations of classical methods that rely on amplitude thresholds calibrated for a specific sensor type. An experimental evaluation of the proposed technique was performed with specially made circular piezopolymer (PVDF) sensors designed for Structural Health Monitoring (SHM) applications, and compared with commercial piezoelectric SHM sensors of similar dimensions. Test impacts at low energies from 35 mJ to 600 mJ were generated in a laboratory by free-falling metal spheres on a 500 mm × 500 mm × 1.25 mm quasi-isotropic Carbon Fiber Reinforced Polymer (CFRP) laminate plate. From the analysis of many impact signals, the resulting localization error was improved for all types of sensors and, in particular, for the circular PVDF sensor an average error of 20.3 mm and a standard deviation of 8.9 mm was obtained. [ABSTRACT FROM AUTHOR]

Localization inWireless Sensor Networks (WSNs) has been an active topic for more than two decades. A variety of algorithms were proposed to improve the localization accuracy. However, they are either limited to two-dimensional (2D) space, or require specific sensor deployment for proper operations. In this paper, we proposed a three-dimensional (3D) localization scheme for WSNs based on the well-known parametric Loop division (PLD) algorithm. The proposed scheme localizes a sensor node in a region bounded by a network of anchor nodes. By iteratively shrinking that region towards its center point, the proposed scheme provides better localization accuracy as compared to existing schemes. Furthermore, it is cost-effective and independent of environmental irregularity. We provide an analytical framework for the proposed scheme and find its lower bound accuracy. Simulation results shows that the proposed algorithm provides an average localization accuracy of 0.89 m with a standard deviation of 1.2 m. [ABSTRACT FROM AUTHOR]

Object tracking and detection is one of the most significant research areas for wireless sensor networks. Existing indoor trajectory tracking schemes in wireless sensor networks are based on continuous localization and moving object data mining. Indoor trajectory tracking based on the received signal strength indicator (RSSI) has received increased attention because it has low cost and requires no special infrastructure. However, RSSI tracking introduces uncertainty because of the inaccuracies of measurement instruments and the irregularities (unstable, multipath, diffraction) of wireless signal transmissions in indoor environments. Heuristic information includes some key factors for trajectory tracking procedures. This paper proposes a novel trajectory tracking scheme based on Delaunay triangulation and heuristic information (TTDH). In this scheme, the entire field is divided into a series of triangular regions. The common side of adjacent triangular regions is regarded as a regional boundary. Our scheme detects heuristic information related to a moving object's trajectory, including boundaries and triangular regions. Then, the trajectory is formed by means of a dynamic time-warping position-fingerprint-matching algorithm with heuristic information constraints. Field experiments show that the average error distance of our scheme is less than 1.5 m, and that error does not accumulate among the regions. [ABSTRACT FROM AUTHOR]

Directional dithering of a laser beam potentially limits the detection accuracy of a laser triangulation displacement probe. A theoretical analysis indicates that the measurement accuracy will linearly decrease as the laser dithering angle increases. To suppress laser dithering, a scheme for reduction of the influence of laser beam directional dithering in a laser triangulation displacement probe, which consists of a collimated red laser, a laser beam pointing control setup, a receiver lens, and a charge-coupled device, is proposed in this paper. The laser beam pointing control setup is inserted into the source laser beam and the measured object and can separate the source laser beam into two symmetrical laser beams. Hence, at the angle at which the source laser beam dithers, the positional averages of the two laser spots are equal and opposite. Moreover, a virtual linear function method is used to maintain a stable average of the positions of the two spots on the imaging side. Experimental results indicate that with laser beam pointing control, the estimated standard deviation of the fitting error decreases from 0.3531mm to 0.0100mm, the repeatability accuracy can be lowered from ±7mm to ±5 μm, and the nonlinear error can be reduced from ±6% FS (full scale) to ±0.16% FS. [ABSTRACT FROM AUTHOR]

The laser triangulation method is one of the most advanced methods for large inner diameter measurement. Our research group proposed a kind of inner diameter measuring device that is principally composed of three laser displacement sensors known to be fixed in the same plane measurement position. It is necessary to calibrate the direction of the laser beams that are emitted by laser displacement sensors because they do not meet the theoretical model accurately. For the purpose of calibrating the direction of laser beams, a calibration method and mathematical model were proposed. The inner diameter measuring device is equipped with the spindle of the machine tool. The laser beams rotate and translate in the plane and constitute the rotary rays which are driven to scan the inner surface of the ring gauge. The direction calibration of the laser beams can be completed by the sensors' distance information and corresponding data processing method. The corresponding error sources are analyzed and the validity of the method is verified. After the calibration, the measurement error of the inner diameter measuring device reduced from -25 μm to -15 μm and the relative error was not more than 0.011%. [ABSTRACT FROM AUTHOR]

High-accuracy surface measurement of large aviation parts is a significant guarantee of aircraft assembly with high quality. The result of boundary measurement is a significant parameter for aviation-part measurement. This paper proposes a measurement method for accurately measuring the surface and boundary of aviation part with feature compression extraction and directed edge-point criterion. To improve the measurement accuracy of both the surface and boundary of large parts, extraction method of global boundary and feature analysis of local stripe are combined. The center feature of laser stripe is obtained with high accuracy and less calculation using a sub-pixel centroid extraction method based on compress processing. This method consists of a compressing process of images and judgment criterion of laser stripe centers. An edge-point extraction method based on directed arc-length criterion is proposed to obtain accurate boundary. Finally, a high-precision reconstruction of aerospace part is achieved. Experiments are performed both in a laboratory and an industrial field. The physical measurements validate that the mean distance deviation of the proposed method is 0.47 mm. The results of the field experimentation show the validity of the proposed method. [ABSTRACT FROM AUTHOR]

State estimation is the most critical capability for MAV (Micro-Aerial Vehicle) localization, autonomous obstacle avoidance, robust flight control and 3D environmental mapping. There are three main challenges for MAV state estimation: (1) it can deal with aggressive 6 DOF (Degree Of Freedom) motion; (2) it should be robust to intermittent GPS (Global Positioning System) (even GPS-denied) situations; (3) it should work well both for low- and high-altitude flight. In this paper, we present a state estimation technique by fusing long-range stereo visual odometry, GPS, barometric and IMU (Inertial Measurement Unit) measurements. The new estimation system has two main parts, a stochastic cloning EKF (Extended Kalman Filter) estimator that loosely fuses both absolute state measurements (GPS, barometer) and the relative state measurements (IMU, visual odometry), and is derived and discussed in detail. A long-range stereo visual odometry is proposed for high-altitude MAV odometry calculation by using both multi-view stereo triangulation and a multi-view stereo inverse depth filter. The odometry takes the EKF information (IMU integral) for robust camera pose tracking and image feature matching, and the stereo odometry output serves as the relative measurements for the update of the state estimation. Experimental results on a benchmark dataset and our real flight dataset show the effectiveness of the proposed state estimation system, especially for the aggressive, intermittent GPS and high-altitude MAV flight. [ABSTRACT FROM AUTHOR]

The Scalar Triangulation and Ranging (STAR) method, which is based upon the unique properties of magnetic gradient contraction, is a high real-time ferromagnetic target localization method. Only one measurement point is required in the STAR method and it is not sensitive to changes in sensing platform orientation. However, the localization accuracy of the method is limited by the asphericity errors and the inaccurate value of position leads to larger errors in the estimation of magnetic moment. To improve the localization accuracy, a modified STAR method is proposed. In the proposed method, the asphericity errors of the traditional STAR method are compensated with an iterative algorithm. The proposed method has a fast convergence rate which meets the requirement of high real-time localization. Simulations and field experiments have been done to evaluate the performance of the proposed method. The results indicate that target parameters estimated by the modified STAR method are more accurate than the traditional STAR method. [ABSTRACT FROM AUTHOR]

Depth image acquisition with structured light approaches in outdoor environments is a challenging problem due to external factors, such as ambient sunlight, which commonly affect the acquisition procedure. This paper presents a novel structured light sensor designed specifically for operation in outdoor environments. The sensor exploits a modulated sequence of structured light projected onto the target scene to counteract environmental factors and estimate a spatial distortion map in a robust manner. The correspondence between the projected pattern and the estimated distortion map is then established using a probabilistic framework based on graphical models. Finally, the depth image of the target scene is reconstructed using a number of reference frames recorded during the calibration process. We evaluate the proposed sensor on experimental data in indoor and outdoor environments and present comparative experiments with other existing methods, as well as commercial sensors. [ABSTRACT FROM AUTHOR]

Modern infrastructure, such as dense urban areas and underground tunnels, can effectively block all GPS signals, which implies that effective position triangulation will not be achieved. The main problem that is addressed in this project is the design and implementation of an accurate vehicle location system using radio-frequency identification (RFID) technology in combination with GPS and the Global system for Mobile communication (GSM) technology, in order to provide a solution to the limitation discussed above. In essence, autonomous vehicle tracking will be facilitated with the use of RFID technology where GPS signals are non-existent. The design of the system and the results are reflected in this paper. An extensive literature study was done on the field known as the Internet of Things, as well as various topics that covered the integration of independent technology in order to address a specific challenge. The proposed system is then designed and implemented. An RFID transponder was successfully designed and a read range of approximately 31 cm was obtained in the low frequency communication range (125 kHz to 134 kHz). The proposed system was designed, implemented, and field tested and it was found that a vehicle could be accurately located and tracked. It is also found that the antenna size of both the RFID reader unit and RFID transponder plays a critical role in the maximum communication range that can be achieved. [ABSTRACT FROM AUTHOR]

To increase the understanding of how the plant phenotype is formed by genotype and environmental interactions, simple and robust high-throughput plant phenotyping methods should be developed and considered. This would not only broaden the application range of phenotyping in the plant research community, but also increase the ability for researchers to study plants in their natural environments. By studying plants in their natural environment in high temporal resolution, more knowledge on how multiple stresses interact in defining the plant phenotype could lead to a better understanding of the interaction between plant responses and epigenetic regulation. In the present paper, we evaluate a commercial 3D NIR-laser scanner (PlantEye, Phenospex B.V., Herleen, The Netherlands) to track daily changes in plant growth with high precision in challenging environments. Firstly, we demonstrate that the NIR laser beam of the scanner does not affect plant photosynthetic performance. Secondly, we demonstrate that it is possible to estimate phenotypic variation amongst the growth pattern of ten genotypes of Brassica napus L. (rapeseed), using a simple linear correlation between scanned parameters and destructive growth measurements. Our results demonstrate the high potential of 3D laser triangulation for simple measurements of phenotypic variation in challenging environments and in a high temporal resolution. [ABSTRACT FROM AUTHOR]

This paper proposes a rapid method to detect aero-engine blade form, according to the characteristics of an aero-engine blade surface. This method first deduces an inclination error model in free-form surface measurements based on the non-contact laser triangulation principle. Then a four-coordinate measuring system was independently developed, a special fixture was designed according to the blade shape features, and a fast measurement of the blade features path was planned. Finally, by using the inclination error model for correction of acquired data, the measurement error that was caused by tilt form is compensated. As a result the measurement accuracy of the Laser Displacement Sensor was less than 10 µm. After the experimental verification, this method makes full use of optical non-contact measurement fast speed, high precision and wide measuring range of features. Using a standard gauge block as a measurement reference, the coordinate system conversion data is simple and practical. It not only improves the measurement accuracy of the blade surface, but also its measurement efficiency. Therefore, this method increases the value of the measurement of complex surfaces. [ABSTRACT FROM AUTHOR]

An alternative authentication method to traditional alphanumeric passwords is graphical password authentication, also known as graphical authentication, for which one of the most valuable cued-recall techniques is PassPoints. This technique stands out for its security and usability. However, it can be violated if the user follows a predefined pattern when selecting the five points in an image as their passwords, such as the DIAG and LINE patterns. Dictionary attacks can be built using these two patterns to compromise graphical passwords. So far, no reports have been found in the state of the art about any test capable of detecting graphical passwords with DIAG or LINE patterns in PassPoints. Studies carried out in other scenarios have shown the effectiveness of the characteristics of Delaunay triangulations in extracting information about the dependence between the points. In this work, graphical passwords formed by five randomly selected points on an image are compared with passwords whose points contain patterns of the DIAG or LINE type. The comparison is based on building for each password its Delaunay triangulation and calculating the mean value of the maximum angles of the triangles obtained; such a mean value is denoted by amadt. It is experimentally shown that in passwords containing DIAG and LINE patterns, the value of amadt is higher than the one obtained in passwords formed by random dots. From this result, it is proposed to use this amadt value as a statistic to build a test of means. This result constitutes the work's main contribution: The proposal of a spatial randomness test to detect weak graphic passwords that contain DIAG and LINE type patterns. The importance and novelty of this result become evident when two aspects are taken into account: First, these weak passwords can be exploited by attackers to improve the effectiveness of their attacks; second, there are no prior criteria to detect this type of weak password. The practical application of said test contributes to increasing PassPoints security without substantially affecting its efficiency. [ABSTRACT FROM AUTHOR]

To automatically evaluate the ergonomics of workers, 3D skeletons are needed. Most ergonomic assessment methods, like REBA, are based on the different 3D joint angles. Thanks to the huge amount of training data, 2D skeleton detectors have become very accurate. In this work, we test three methods to calculate 3D skeletons from 2D detections: using the depth from a single RealSense range camera, triangulating the joints using multiple cameras, and combining the triangulation of multiple camera pairs. We tested the methods using recordings of a person doing different assembly tasks. We compared the resulting joint angles to the ground truth of a VICON marker-based tracking system. The resulting RMS angle error for the triangulation methods is between 12° and 16°, showing that they are accurate enough to calculate a useful ergonomic score from. [ABSTRACT FROM AUTHOR]

Distributed sensing, computing and communication capabilities of wireless sensor networks require, in most situations, an efficient node localization procedure. In the case of random deployments in harsh or hostile environments, a general localization process within global coordinates is based on a set of anchor nodes able to determine their own position using GPS receivers. In this paper we propose another anchor node localization technique that can be used when GPS devices cannot accomplish their mission or are considered to be too expensive. This novel technique is based on the fusion of video and compass data acquired by the anchor nodes and is especially suitable for video- or multimedia-based wireless sensor networks. For these types of wireless networks the presence of video cameras is intrinsic, while the presence of digital compasses is also required for identifying the cameras' orientations. [ABSTRACT FROM AUTHOR]

This work discusses a novel approach to image acquisition which improves the robustness of captured data required for 3D range measurements. By applying a pseudo-random code modulation to sequential acquisition of projected patterns the impact of environmental factors such as ambient light and mutual interference is significantly reduced. The proposed concept has been proven with an experimental range sensor based on the laser triangulation principle. The proposed design can potentially enhance the use of this principle to a variety of outdoor applications, such as autonomous vehicles, pedestrians' safety, collision avoidance, and many other tasks, where robust real-time distance detection in real world environment is crucial. [ABSTRACT FROM AUTHOR]

The aim of the research is to analyze the possibility of the development and realization of a common laser triangulation sensor arrangement-based probe for the measurement of slots and bore sides with the help of a mirror attachment. The analysis shows the feasibility and limits of the solution with respect to the maximum measurement depth and surface distance measurement working range. We propose two possible solutions: one for maximizing the ratio of the measurement depth to the measured bore size and the second for maximizing the total depth, intended for the measurement of slots and large bore sizes. We analyzed measurement error sources. We found that the errors related to the reflection mirror misalignment can be fully compensated. We proved the validity of the proposed solution with the realization of a commercial laser triangulation sensor-based probe and demonstrated a slot side and a bore side surface distance scanning measurement. The probe working range was assessed with regard to the obscuration effect of optical beams. [ABSTRACT FROM AUTHOR]

Due to pathologies or age-related problems, in some disabled people, motor impairment is associated with cognitive and/or visual impairments. This combination of limitations unfortunately leads to an inability to move around independently. Indeed, their situation does not allow them to use a conventional electric wheelchair, for safety reasons, and for the moment there is no other technological solution providing safe movement capacity. This lack of access to an autonomous travel solution has the consequence of weakening the intellectual, personal, social, cultural and moral development, as well as the life expectancy, of the people concerned. In this context, our team is working on the development of an optoelectronic system that secures the displacement of electric wheelchairs. This is a large project that requires the development of several functionalities such as: the anti-collision of the wheelchair with its environment, the prevention of falls from the wheelchair on uneven levels, and the adaptation of the system mechanically and electronically to the majority of commercially available electric wheelchair models, among others. In this article, we introduce our solution for detecting dangerous height differences, also called "negative obstacles", through the creation of a dedicated sensor. This sensor works by optical triangulation and can embed several laser beams in order to extend its detection zone. It has the particularity of being robust in direct sunlight and rain and has a sufficiently high measurement rate to be suitable for the displacement of electric wheelchairs. We develop an adapted algorithm, and point out compromises, in particular between the orientation of the laser beams and the maximal speed of the wheelchair. [ABSTRACT FROM AUTHOR]

One of the most critical issues of Wireless Sensor Networks (WSNs) is the deployment of a limited number of sensors in order to achieve maximum coverage on a terrain. The optimal sensor deployment which enables one to minimize the consumed energy, communication time and manpower for the maintenance of the network has attracted interest with the increased number of studies conducted on the subject in the last decade. Most of the studies in the literature today are proposed for two dimensional (2D) surfaces; however, real world sensor deployments often arise on three dimensional (3D) environments. In this paper, a guided wavelet transform (WT) based deployment strategy (WTDS) for 3D terrains, in which the sensor movements are carried out within the mutation phase of the genetic algorithms (GAs) is proposed. The proposed algorithm aims to maximize the Quality of Coverage (QoC) of a WSN via deploying a limited number of sensors on a 3D surface by utilizing a probabilistic sensing model and the Bresenham's line of sight (LOS) algorithm. In addition, the method followed in this paper is novel to the literature and the performance of the proposed algorithm is compared with the Delaunay Triangulation (DT) method as well as a standard genetic algorithm based method and the results reveal that the proposed method is a more powerful and more successful method for sensor deployment on 3D terrains. [ABSTRACT FROM AUTHOR]

The non-invasive inspection of surfaces is a major issue in a wide variety of industries and research laboratories. The vast and increasing range of surface types, tolerance requirements and measurement constraints demanded during the last decades represents a major research effort in the development of new methods, systems and metrological strategies. The discreet dimensional evaluation the rugometric characterization and the profilometric inspection seem to be insufficient in many instances. The full microtopographic inspection has became a common requirement. Among the different systems developed, optical methods have the most important role and among those triangulation-based ones have gained a major status thanks to their flexibility, reliability and robustness. In this communication we will provide a brief historical review on the development of optical triangulation application to the dimensional inspection of objects and surfaces and on the work done at the Microtopography Laboratory of the Physics Department of the University of Minho, Portugal, in the development of methods and systems of optical triangulation-based microtopographic inspection of surfaces. [ABSTRACT FROM AUTHOR]

Consumer-grade range cameras such as the Kinect sensor have the potential to be used in mapping applications where accuracy requirements are less strict. To realize this potential insight into the geometric quality of the data acquired by the sensor is essential. In this paper we discuss the calibration of the Kinect sensor, and provide an analysis of the accuracy and resolution of its depth data. Based on a mathematical model of depth measurement from disparity a theoretical error analysis is presented, which provides an insight into the factors influencing the accuracy of the data. Experimental results show that the random error of depth measurement increases with increasing distance to the sensor, and ranges from a few millimeters up to about 4 cm at the maximum range of the sensor. The quality of the data is also found to be influenced by the low resolution of the depth measurements. [ABSTRACT FROM AUTHOR]

Sensing and communication coverage are among the most important trade-offs in Wireless Sensor Network (WSN) design. A minimum bound of sensing coverage is vital in scheduling, target tracking and redeployment phases, as well as providing communication coverage. Some methods measure the coverage as a percentage value, but detailed information has been missing. Two scenarios with equal coverage percentage may not have the same Quality of Coverage (QoC). In this paper, we propose a new coverage measurement method using Delaunay Triangulation (DT). This can provide the value for all coverage measurement tools. Moreover, it categorizes sensors as 'fat', 'healthy' or 'thin' to show the dense, optimal and scattered areas. It can also yield the largest empty area of sensors in the field. Simulation results show that the proposed DT method can achieve accurate coverage information, and provides many tools to compare QoC between different scenarios. [ABSTRACT FROM AUTHOR]

In this paper, a stereo vision 3D position measurement system for a three-axial pneumatic parallel mechanism robot arm is presented. The stereo vision 3D position measurement system aims to measure the 3D trajectories of the end-effector of the robot arm. To track the end-effector of the robot arm, the circle detection algorithm is used to detect the desired target and the SAD algorithm is used to track the moving target and to search the corresponding target location along the conjugate epipolar line in the stereo pair. After camera calibration, both intrinsic and extrinsic parameters of the stereo rig can be obtained, so images can be rectified according to the camera parameters. Thus, through the epipolar rectification, the stereo matching process is reduced to a horizontal search along the conjugate epipolar line. Finally, 3D trajectories of the end-effector are computed by stereo triangulation. The experimental results show that the stereo vision 3D position measurement system proposed in this paper can successfully track and measure the fifth-order polynomial trajectory and sinusoidal trajectory of the end-effector of the three- axial pneumatic parallel mechanism robot arm. [ABSTRACT FROM AUTHOR]

Welding is a very complex process in which the final weld quality can be affected by many process parameters. In order to inspect the weld quality and detect the presence of various weld defects, different methods and systems are studied and developed. In this paper, a laser-based vision system is developed for non-destructive weld quality inspection. The vision sensor is designed based on the principle of laser triangulation. By processing the images acquired from the vision sensor, the geometrical features of the weld can be obtained. Through the visual analysis of the acquired 3D profiles of the weld, the presences as well as the positions and sizes of the weld defects can be accurately identified and therefore, the non-destructive weld quality inspection can be achieved. [ABSTRACT FROM AUTHOR]

A technique for intrinsic and extrinsic calibration of a laser triangulation sensor (LTS) integrated in an articulated arm coordinate measuring machine (AACMM) is presented in this paper. After applying a novel approach to the AACMM kinematic parameter identification problem, by means of a single calibration gauge object, a one-step calibration method to obtain both intrinsic--laser plane, CCD sensor and camera geometry--and extrinsic parameters related to the AACMM main frame has been developed. This allows the integration of LTS and AACMM mathematical models without the need of additional optimization methods after the prior sensor calibration, usually done in a coordinate measuring machine (CMM) before the assembly of the sensor in the arm. The experimental tests results for accuracy and repeatability show the suitable performance of this technique, resulting in a reliable, quick and friendly calibration method for the AACMM final user. The presented method is also valid for sensor integration in robot arms and CMMs. [ABSTRACT FROM AUTHOR]

On-line non-contact surface inspection with high precision is still an open problem. Laser triangulation techniques are the most common solution for this kind of systems, but there exist fundamental limitations to their applicability when high precisions, long standoffs or large apertures are needed, and when there are difficult operating conditions. Other methods are, in general, not applicable in hostile environments or inadequate for on-line measurement. In this paper we review the latest research in Conoscopic Holography, an interferometric technique that has been applied successfully in this kind of applications, ranging from submicrometric roughness measurements, to long standoff sensors for surface defect detection in steel at high temperatures. [ABSTRACT FROM AUTHOR]

Passive ground emitter geolocation techniques are essential to electronic warfare systems, as they provide threat warnings in hostile environments, while ensuring the electronic silence of the mission platform. Geolocation of enemy emitters indicates the position of and type of adversary troops, and allows for the use of guided munition against enemy targets. Three-dimensional geolocation solutions based on least squares and particle filter estimation, using only azimuth and elevation measurements, were considered. Three batch-processing and one instantaneous solution algorithms, i.e., using a single pulse or a single observation point, were developed and investigated. The performance of the proposed solutions was demonstrated by simulations. Results showed that the batch-processing solutions achieved acceptable accuracies with a sufficient number of observation points. The performance degraded with fewer observation points. The instantaneous geolocation solution improved performance with increasing observation points, i.e., working in the sequential mode, and therefore could approach the accuracy of the batch-processing solutions. [ABSTRACT FROM AUTHOR]

In a 3D scanning system, using a camera and a line laser, it is critical to obtain the exact geometrical relationship between the camera and laser for precise 3D reconstruction. With existing depth cameras, it is difficult to scan a large object or multiple objects in a wide area because only a limited area can be scanned at a time. We developed a 3D scanning system with a rotating line laser and wide-angle camera for large-area reconstruction. To obtain 3D information of an object using a rotating line laser, we must be aware of the plane of the line laser with respect to the camera coordinates at every rotating angle. This is done by estimating the rotation axis during calibration and then by rotating the laser at a predefined angle. Therefore, accurate calibration is crucial for 3D reconstruction. In this study, we propose a calibration method to estimate the geometrical relationship between the rotation axis of the line laser and the camera. Using the proposed method, we could accurately estimate the center of a cone or cylinder shape generated while the line laser was rotating. A simulation study was conducted to evaluate the accuracy of the calibration. In the experiment, we compared the results of the 3D reconstruction using our system and a commercial depth camera. The results show that the precision of our system is approximately 65% higher for plane reconstruction, and the scanning quality is also much better than that of the depth camera. [ABSTRACT FROM AUTHOR]

In this paper, we investigated the effect of the incidence angle of a laser ray on the reflected laser intensity. A dataset on this dependence is presented for materials usually used in the industry, such as transparent and non-transparent plastics and aluminum alloys with different surface roughness. The measurements have been performed with a laser line triangulation sensor and a UR10e robot. The presented results are proposing where to place the sensor relative to the scanned object, thus increasing the reliability of the sensor data collection. [ABSTRACT FROM AUTHOR]

The demand for extensive gear shape measurements with single-digit µm uncertainty is growing. Tactile standard gear tests are precise but limited in speed. Recently, faster optical gear shape measurement systems have been examined. Optical gear shape measurements are challenging due to potential deviation sources such as the tilt angles between the surface normal and the sensor axis, the varying surface curvature, and the surface properties. Currently, the full potential of optical gear shape measurement systems is not known. Therefore, laser triangulation and confocal-chromatic gear shape measurements using a lateral scanning position measurement approach are studied. As a result of tooth flank standard measurements, random effects due to surface properties are identified to primarily dominate the achievable gear shape measurement uncertainty. The standard measurement uncertainty with the studied triangulation sensor amounts to >10 µm, which does not meet the requirements. The standard measurement uncertainty with the confocal-chromatic sensor is <6.5 µm. Furthermore, measurements on a spur gear show that multiple reflections do not influence the measurement uncertainty when measuring with the lateral scanning position measurement approach. Although commercial optical sensors are not designed for optical gear shape measurements, standard uncertainties of <10 µm are achievable for example with the applied confocal-chromatic sensor, which indicates the further potential for optical gear shape measurements. [ABSTRACT FROM AUTHOR]

Laser triangulation sensors (LTS) are widely used to acquire depth information in industrial applications. However, the parameters of the components, e.g., the camera, of the off-the-shelf LTS are typically unknown. This makes it difficult to recalibrate the degenerated LTS devices during regular maintenance operations. In this paper, a novel one-dimensional target-based camera intrinsic matrix-free LTS calibration method is proposed. In contrast to conventional methods that calibrate the LTS based on the precise camera intrinsic matrix, we formulate the LTS calibration as an optimization problem taking all parameters of the LTS into account, simultaneously. In this way, many pairs of the camera intrinsic matrix and the equation of the laser plane can be solved and different pairs of parameters are equivalent for displacement measurement. A closed-form solution of the position of the one-dimensional target is proposed to make the parameters of the LTS optimizable. The results of simulations and experiments show that the proposed method can calibrate the LTS without knowing the camera intrinsic matrix. In addition, the proposed approach significantly improves the displacement measurement precision of the LTS after calibration. In conclusion, the proposed method proved that the precise camera intrinsic matrix is not the necessary condition for LTS displacement measurement. [ABSTRACT FROM AUTHOR]

With the popularity of portable positioning devices, crowd-sourced trajectory data have attracted widespread attention, and led to many research breakthroughs in the field of road network extraction. However, it is still a challenging task to detect the road networks of old downtown areas with complex network layouts from high noise, low frequency, and uneven distribution trajectories. Therefore, this paper focuses on the old downtown area and provides a novel intersection-first approach to generate road networks based on low quality, crowd-sourced vehicle trajectories. For intersection detection, virtual representative points with distance constraints are detected, and the clustering by fast search and find of density peaks (CFDP) algorithm is introduced to overcome low frequency features of trajectories, and improve the positioning accuracy of intersections. For link extraction, an identification strategy based on the Delaunay triangulation network is developed to quickly filter out false links between large-scale intersections. In order to alleviate the curse of sparse and uneven data distribution, an adaptive link-fitting scheme, considering feature differences, is further designed to derive link centerlines. The experiment results show that the method proposed in this paper preforms remarkably better in both intersection detection and road network generation for old downtown areas. [ABSTRACT FROM AUTHOR]

The purpose of this research was to develop a simple, cost-effective, but enough efficient solution for locating, tracking and distribution analysis of people and/or vehicle flowing, based on non-intrusive Bluetooth sensing and selective filtering algorithms employing artificial intelligence components. The solution provides a tool for analyzing density of targets in a specific area, useful when checking contact proximities of a target along a route. The principle consists of the detection of mobile devices that use active Bluetooth connections, such as personal notebooks, smartphones, smartwatches, Bluetooth headphones, etc. to locate and track their movement in the dedicated area. For this purpose, a specific configuration of three BT sensors is used and RSSI levels compared, based on a combination of differential location estimates. The solution may also be suited for indoor localization where GPS signals are usually weak or missing; for example, in public places such as subway stations or trains, hospitals, airport terminals and so on. The applicability of this solution is estimated to be vast, ranging from travel and transport information services, route guidance, passenger flows tracking, and path recovery for persons suspected to have SARS-COV2 or other contagious viruses, serving epidemiologic enquiries. The specific configuration of Bluetooth detectors may be installed either in a fixed location, or in a public transport vehicle. A set of filters and algorithms for triangulation-based location of detected targets and movement tracking, based on artificial intelligence is employed. When applied in the public transport field, this setup can be also developed to extract additional information on traffic, such as private traffic flowing, or passenger movement patterns along the vehicle route, improved location in absence of GPS signals, etc. Field tests have been carried out for determining different aspects concerning indoor location accuracy, reliability, selection of targets and filtering. Results and possible applications are also presented in the final section of the paper. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) triangulation based on active binocular vision has increasing amounts of applications in computer vision and robotics. An active binocular vision system with non-fixed cameras needs to calibrate the stereo extrinsic parameters online to perform 3D triangulation. However, the accuracy of stereo extrinsic parameters and disparity have a significant impact on 3D triangulation precision. We propose a novel eye gaze based 3D triangulation method that does not use stereo extrinsic parameters directly in order to reduce the impact. Instead, we drive both cameras to gaze at a 3D spatial point P at the optical center through visual servoing. Subsequently, we can obtain the 3D coordinates of P through the intersection of the two optical axes of both cameras. We have performed experiments to compare with previous disparity based work, named the integrated two-pose calibration (ITPC) method, using our robotic bionic eyes. The experiments show that our method achieves comparable results with ITPC. [ABSTRACT FROM AUTHOR]

Rail surface scratching occurs with increasing frequency, seriously threatening the safety of vehicles and humans. Online repair of rail-surface scratches on damaged rails with scratch depths >1 mm is of increased importance, because direct rail-replacement has the disadvantages of long operation time, high manpower and high material costs. Advanced online repair of rail-surface scratch using three-dimensional (3D) metal printing technology such as laser cladding has become an increasing trend, desperately demanding a solution for the fast and precise establishment of a complete closed mesh model of rail-surface scratch data. However, there have only been limited studies on the topic so far. In this paper, the complete closed mesh model is well established based on a novel triangulation algorithm relying on the topological features of the point-cloud model (PCM) of scratch-data, which is obtained by implementing a scratch-data-computation process following a rail-geometric-feature-fused algorithm of random sample consensus (RANSAC) performed on the full rail-surface PCM constructed by 3D laser vision. The proposed method is universal for all types of normal-speed rails in China. Experimental results show that the proposed method can accurately acquire the complete closed mesh models of scratch data of one meter of 50 Kg/m-rails within 1 min. [ABSTRACT FROM AUTHOR]

Absolute distance measurement is a field of research with a large variety of applications. Laser triangulation is a well-tested and developed technique using geometric relations to calculate the absolute distance to an object. The advantages of laser triangulation include its simple and cost-effective setup with yet a high achievable accuracy and resolution in short distances. A main problem of the technology is that even small changes of the optomechanical setup, e.g., due to thermal expansion, lead to significant measurement errors. Therefore, in this work, we introduce an optical setup containing only a beam splitter and a mirror, which splits the laser into a measurement beam and a reference beam. The reference beam can then be used to compensate for different error sources, such as laser beam dithering or shifts of the measurement setup due to the thermal expansion of the components. The effectiveness of this setup is proven by extensive simulations and measurements. The compensation setup improves the deviation in static measurements by up to 75%, whereas the measurement uncertainty at a distance of 1 m can be reduced to 85 μm. Consequently, this compensation setup can improve the accuracy of classical laser triangulation devices and make them more robust against changes in environmental conditions. [ABSTRACT FROM AUTHOR]

This paper deals with the design of a decentralized guidance and control strategy for a swarm of unmanned aerial vehicles (UAVs), with the objective of maintaining a given connection topology with assigned mutual distances while flying to a target area. In the absence of obstacles, the assigned topology, based on an extended Delaunay triangulation concept, implements regular and connected formation shapes. In the presence of obstacles, this technique is combined with a model predictive control (MPC) that allows forming independent sub-swarms optimizing the formation spreading to avoid obstacles and collisions between neighboring vehicles. A custom numerical simulator was developed in a Matlab/Simulink environment to prove the effectiveness of the proposed guidance and control scheme in several 2D operational scenarios with obstacles of different sizes and increasing number of aircraft. [ABSTRACT FROM AUTHOR]

Scanning electron microscopes (SEMs) are versatile imaging devices for the micro- and nanoscale that find application in various disciplines such as the characterization of biological, mineral or mechanical specimen. Even though the specimen's two-dimensional (2D) properties are provided by the acquired images, detailed morphological characterizations require knowledge about the three-dimensional (3D) surface structure. To overcome this limitation, a reconstruction routine is presented that allows the quantitative depth reconstruction from SEM image sequences. Based on the SEM's imaging properties that can be well described by an affine camera, the proposed algorithms rely on the use of affine epipolar geometry, self-calibration via factorization and triangulation from dense correspondences. To yield the highest robustness and accuracy, different sub-models of the affine camera are applied to the SEM images and the obtained results are directly compared to confocal laser scanning microscope (CLSM) measurements to identify the ideal parametrization and underlying algorithms. To solve the rectification problem for stereo-pair images of an affine camera so that dense matching algorithms can be applied, existing approaches are adapted and extended to further enhance the yielded results. The evaluations of this study allow to specify the applicability of the affine camera models to SEM images and what accuracies can be expected for reconstruction routines based on self-calibration and dense matching algorithms. [ABSTRACT FROM AUTHOR]

A laser triangulation system, which is composed of a camera and a laser, calculates distances between objects intersected by the laser plane. Even though there are commercial triangulation systems, developing a new system allows the design to be adapted to the needs, in addition to allowing dimensions or processing times to be optimized; however the disadvantage is that the real accuracy is not known. The aim of the research is to identify and discuss the relevance of the most significant error sources in laser triangulator systems, predicting their error contribution to the final joint measurement accuracy. Two main phases are considered in this study, namely the calibration and measurement processes. The main error sources are identified and characterized throughout both phases, and a synthetic error propagation methodology is proposed to study the measurement accuracy. As a novelty in uncertainty analysis, the present approach encompasses the covariances of correlated system variables, characterizing both phases for a laser triangulator. An experimental methodology is adopted to evaluate the measurement accuracy in a laser triangulator, comparing it with the values obtained with the synthetic error propagation methodology. The relevance of each error source is discussed, as well as the accuracy of the error propagation. A linearity value of 40 µm and maximum error of 0.6 mm are observed for a 100 mm measuring range, with the camera calibration phase being the main error contributor. [ABSTRACT FROM AUTHOR]

In spatial data with complexity, different clusters can be very contiguous, and the density of each cluster can be arbitrary and uneven. In addition, background noise that does not belong to any clusters in the data, or chain noise that connects multiple clusters may be included. This makes it difficult to separate clusters in contact with adjacent clusters, so a new approach is required to solve the nonlinear shape, irregular density, and touching problems of adjacent clusters that are common in complex spatial data clustering, as well as to improve robustness against various types of noise in spatial clusters. Accordingly, we proposed an efficient graph-based spatial clustering technique that employs Delaunay triangulation and the mechanism of DBSCAN (density-based spatial clustering of applications with noise). In the performance evaluation using simulated synthetic data as well as real 3D point clouds, the proposed method maintained better clustering and separability of neighboring clusters compared to other clustering techniques, and is expected to be of practical use in the field of spatial data mining. [ABSTRACT FROM AUTHOR]

The 2D point location problem has applications in several areas, such as geographic information systems, navigation systems, motion planning, mapping, military strategy, location and tracking moves. We aim to present a new approach that expands upon current techniques and methods to locate the 2D position of a signal source sent by an emitter device. This new approach is based only on the geometric relationship between an emitter device and a system composed of m ≥ 2 signal receiving devices. Current approaches applied to locate an emitter can be deterministic, statistical or machine-learning methods. We propose to perform this triangulation by geometric models that exploit elements of pole-polar geometry. For this purpose, we are presenting five geometric models to solve the point location problem: (1) based on centroid of points of pole-polar geometry, PPC; (2) based on convex hull region among pole-points, CHC; (3) based on centroid of points obtained by polar-lines intersections, PLI; (4) based on centroid of points obtained by tangent lines intersections, TLI; (5) based on centroid of points obtained by tangent lines intersections with minimal angles, MAI. The first one has computational cost O (n) and whereas has the computational cost O (n l o g n) where n is the number of points of interest. [ABSTRACT FROM AUTHOR]

To better solve the problem of target detection in marine environment and to deal with the difficulty of 3D reconstruction of underwater target, a binocular vision-based underwater target detection and 3D reconstruction system is proposed in this paper. Two optical sensors are used as the vision of the system. Firstly, denoising and color restoration are performed on the image sequence acquired by the vision of the system and the underwater target is segmented and extracted according to the image saliency using the super-pixel segmentation method. Secondly, aiming to reduce mismatch, we improve the semi-global stereo matching method by strictly constraining the matching in the valid target area and then optimizing the basic disparity map within each super-pixel area using the least squares fitting interpolation method. Finally, based on the optimized disparity map, triangulation principle is used to calculate the three-dimensional data of the target and the 3D structure and color information of the target can be given by MeshLab. The experimental results show that for a specific size underwater target, the system can achieve higher measurement accuracy and better 3D reconstruction effect within a suitable distance. [ABSTRACT FROM AUTHOR]

Laser triangulation (LT) is widely used in many fields due to its good stability, high resolution and fast speed. However, the accuracy in these applications suffers from severe constraints on the data acquisition accuracy of LT. To solve this problem, the optical triangulation principle, the object equation of the optical path relationship and the deviation of the laser spot centroid are applied to deduce a mathematical model. Therefore, the image sensor inclination errors can be quantitatively calculated, and the collected data are compensated in real time. Further, a threshold sub-pixel gray-gravity (GG) extraction algorithm is proposed; the gradient function and Gaussian fit algorithm are used to set thresholds to remove the impact of the spot edge noise area on the center location; and polynomial interpolation is employed to enhance the data density of the traditional GG method, thus improving the data acquisition accuracy of LT. Finally, the above methods are applied to on-machine measurement of the American Petroleum Institute (API) thread and the screw rotor, respectively. The experimental results prove that the proposed method can significantly improve the measurement accuracy of free-form curved surfaces using LT and that the improved laser spot center extraction algorithm is more suitable for free-form curved surfaces with smaller curvature and more uniform curvature changes. [ABSTRACT FROM AUTHOR]