Laser Vision System Research Articles

A Ship Cargo Hold Inspection Approach Using Laser Vision Systems

Our paper represents a vision system based on the laser measurement system (LMS) for bulk ship inspection. The LMS scanner with 2-axis servo system is installed on the ship loader to build the shape of the ship. Then, a group of real-time image processing algorithms are implemented to compute the shape of the cargo hold, the inclination angle of the ship and the relative position between the ship loader and the cargo hold. Based on those computed inspection data of the ship, the ship loader can accomplish the bulk cargo loading operation automatically. Finally, our paper describes and analyzes the experiment of the Laser Vision System in Coal Terminal of Tianjin Port. DOI: http://dx.doi.org/10.11591/telkomnika.v11i1.1904

Embedded Laser Vision System for Indoor Aerial Autonomous Navigation

An embedded laser vision system for indoor autonomous navigation of an Unmanned Aerial Vehicle (UAV) is presented. The vision system is composed of a camera, a classical laser line and vision algorithms and it estimates its distance and its heading with respect to a wall placed in front of the camera frame. The image processing is executed onboard and the obtained measures are sent to the microprocessor to compute the control algorithms. A flight simulator is developed in order to validate the control strategy. Additionally, flight tests are carried out in order to prove the efficiency of the closed-loop system.

Accurate measurement method of the thickness of a quartz pendulous reed by combining polarized reflectance and vision image

The detection of thickness provides important information on the production process of the quartz pendulous reed (QRP). Through real-time detection of QPR thickness, high-quality products can be produced, and defective products can be identified and removed. In order to improve detection accuracy and efficiency, a novel noncontact method for measuring the QPR thickness by combining the polarized reflectance and vision image is presented, which can be automated. Based on Snell’s law of fundamental optics, the image of the laser spot is obtained by a laser vision system. The selection criterion of the laser incident angle is analyzed. An improved edge detection algorithm is proposed to locate the subpixel edge of the laser spot, and the calculation method of the laser spot center is presented based on a set of subpixel edge-point data obtained by defining an error function which is to optimize the distribution of data points and minimize it. Experimental results show that the method proposed has good stability and high measurement accuracy, which can achieve noncontact accurate measurement of QPR thickness.

Towards semi-autonomous operation of under-actuated underwater vehicles: sensor fusion, on-line identification and visual servo control

In this paper we propose a framework for semi-autonomous operation of an under-actuated underwater vehicle. The contributions of this paper are twofold: The first contribution is a visual servoing control scheme that is designed to provide a human operator the capability to steer the vehicle without loosing the target from the vision system's field of view. It is shown that the under-actuated degree of freedom is input-to-state stable (ISS) and a shaping of the user input with stability guarantees is implemented. The resulting control scheme has formally guaranteed stability and convergence properties. The second contribution is an asynchronous Modified Dual Unscented Kalman Filter (MDUKF) for the on-line state and parameter estimation of the vehicle by fusing data from a Laser Vision System (LVS) and an Inertial Measurement Unit (IMU). The MDUKF has been developed in order to experimentally verify the performance of the proposed visual servoing control scheme. Experimental results of the visual servoing control scheme integrated with the asynchronous MDUKF indicate the feasibility and applicability of the proposed control scheme. Experiments have been carried out on a small under-actuated Remotely Operated Vehicle (ROV) in a test tank.

Integrated System for Autonomous Proximity Operations and Docking

An integrated system composed of guidance, navigation and control (GNC) system for autonomous proximity operations and the docking of two spacecraft was developed. The position maneuvers were determined through the integration of the statedependent Riccati equation formulated from nonlinear relative motion dynamics and relative navigation using rendezvous laser vision (Lidar) and a vision sensor system. In the vision sensor system, a switch between sensors was made along the approach phase in order to provide continuously effective navigation. As an extension of the rendezvous laser vision system, an automated terminal guidance scheme based on the Clohessy-Wiltshire state transition matrix was used to formulate a “V-bar hopping approach” reference trajectory. A proximity operations strategy was then adapted from the approach strategy used with the automated transfer vehicle. The attitude maneuvers, determined from a linear quadratic Gaussian-type control including quaternion based attitude estimation using star trackers or a vision sensor system, provided precise attitude control and robustness under uncertainties in the moments of inertia and external disturbances. These functions were then integrated into an autonomous GNC system that can perform proximity operations and meet all conditions for successful docking. A sixdegree of freedom simulation was used to demonstrate the effectiveness of the integrated system.

Ariane rocket nozzles welded using British laser vision system

Ariane rocket nozzles welded using British laser vision system

Reconstruction of 3D contour with an active laser-vision robotic system

This paper presents a 3D contour reconstruction approach employing a wheeled mobile robot equipped with an active laser-vision system. With observation from an onboard CCD camera, a laser line projector fixed-mounted below the camera is used for detecting the bottom shape of an object while an actively-controlled upper laser line projector is utilized for 3D contour reconstruction. The mobile robot is driven to move around the object by a visual servoing and localization technique while the 3D contour of the object is being reconstructed based on the 2D image of the projected laser line. Asymptotical convergence of the closed-loop system has been established. The proposed algorithm also has been used experimentally with a Dr Robot X80sv mobile robot upgraded with the low-cost active laser-vision system, thereby demonstrating effective real-time performance. This seemingly novel laser-vision robotic system can be applied further in unknown environments for obstacle avoidance and guidance control tasks. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society

Design of structural health monitoring robot using modified structured light

Localisation and map building of mobile robots are key technologies in implementing autonomous navigation systems. Because of many efforts in the past decade it has proved that simultaneous localisation and map building (SLAM) is possible both theoretically and practically. Features or landmarks obtained from sensor measurements are registered and associated in SLAM if they are sustainable and correctly matched ones. To have such features it is essential to use a sensor system that provides precise range measurements. Typical sensors for SLAM includes the laser range finder (LIDAR), ultra sonic and vision sensor. LIDARs provide very accurate and long range measurements whereas measurements from ultrasonic sensors are shorter and coarse due to cone shaped beam patterns. In this article, a structured light system, which combines laser and vision is thus considered for use with structural displacement measurement. This article proposes a multiple dual laser-vision system to be used as a structural displaceme...

Motion and Parameter Estimation of Space Objects Using Laser-Vision Data

free-falling tumbling satellite (target). The filter receives only noisy pose measurements from a laser-vision system aboard another satellite (chaser) at a close distance in a neighboring orbit. The filter estimates the full states, all the inertia parameters of the target satellite, and the covariance of the measurement noise. A comprehensive dynamics model that includes aspects of orbital mechanics is incorporated for accurate estimation. The discrete-time model, whichinvolvesastate-transitionmatrixandthecovarianceofprocessnoise,isderivedinclosedform,thusrendering the filtersuitableforreal-timeimplementation.Thestatisticalcharacteristicsofthemeasurementnoiseisformulated by a state-dependent covariance matrix. This model allows additive quaternion noise, while preserving the unitnorm property of the quaternion. The convergence properties of the developed filter is demonstrated by simulation andexperimental results. These results also demonstrate that the filter can continuously produce accurate estimates of pose even when the vision system is occluded for tens of seconds.

Binary Weighted Averaging of an Ensemble of Coherently Collected Image Frames

Recent interest in the collection of remote laser radar imagery has motivated novel systems that process temporally contiguous frames of collected imagery to produce an average image that reduces laser speckle, increases image SNR, decreases the deleterious effects of atmospheric distortion, and enhances image detail. This research seeks an algorithm based on Bayesian estimation theory to select those frames from an ensemble that increases spatial resolution compared to simple unweighted averaging of all frames. The resulting binary weighted motion-compensated frame average is compared to the unweighted average using simulated and experimental data collected from a fielded laser vision system. Image resolution is significantly enhanced as quantified by the estimation of the atmospheric seeing parameter through which the average image was formed.

Compensation of installation errors in a laser vision system and dimensional inspection of automobile chassis

Laser vision inspection systems are becoming popular for automated inspection of manufactured components. The performance of such systems can be enhanced by improving accuracy of the hardware and robustness of the software used in the system. This paper presents a new approach for enhancing the capability of a laser vision system by applying hardware compensation and using efficient analysis software. A 3D geometrical model is developed to study and compensate for possible distortions in installation of gantry robot on which the vision system is mounted. Appropriate compensation is applied to the inspection data obtained from the laser vision system based on the parameters in 3D model. The present laser vision system is used for dimensional inspection of car chassis sub frame and lower arm assembly module. An algorithm based on simplex search techniques is used for analyzing the compensated inspection data. The details of 3D model, parameters used for compensation and the measurement data obtained from the system are presented in this paper. The details of search algorithm used for analyzing the measurement data and the results obtained are also presented in the paper. It is observed from the results that, by applying compensation and using appropriate algorithms for analyzing, the error in evaluation of the inspection data can be significantly minimized, thus reducing the risk of rejecting good parts.

Determination and mapping of measurement and design coordinate systems using computational geometric techniques

Automotive industry is one of the most prospective manufacturing industries in the present world. In order to keep up with the challenges of competitors, the automobile industries are taking necessary steps to satisfy the customers by supplying products of good quality at lower cost. The machine vision inspection systems play an important role in quality control with their accurate dimensional measurement capability. The data obtained from these systems have to be analyzed using appropriate algorithms. In the present work, algorithms based on computational geometric techniques have been developed, to set up the coordinate system for the data obtained from the laser vision system for subframe and lower arm assembly of automobile front chassis module. The concept of a convex hull and a modified Voronoi diagram are utilized for establishing the coordinate system for measurement data. The design coordinate system is determined using the Voronoi diagrams. The measurement and design coordinate systems are mapped using 3D transformations. The results obtained for the sample data are also presented in this paper.

Automatic machine vision calibration using statistical and neural network methods

A methodology is presented for camera calibration that is designed to improve the accuracy of machine vision based object measurement systems. The regression and artificial neural network techniques studied are considered to be complimentary rather than competitive. Neural networks have been identified as being particularly useful for the precise modelling of non-linear response, and offer the additional benefits of being non-prescriptive and generally applicable to factors such as radial lens distortion, manufacturing errors and minor camera misalignments. The combination of these modelling techniques within automated program control strategy is suggested as a new approach for straightforward and accessible machine vision calibration. The method has particularly good application to vision metrology and reverse engineering tasks. A demonstrator system has been constructed, employing a scanning laser line and vision system for object measurement in three-dimensions. Experimental results are presented along with a demonstration of the reduction in measurement error that can be attained through the application of regression analysis and artificial neural network modelling.

Hybrid algorithm for determination of dimensional accuracy of automobile front chassis module using laser measurement data

Measurement data obtained from an inspection system need to be analyzed using appropriate algorithms to estimate dimensional errors and to obtain reliable inspection results. This paper proposes a hybrid algorithm based on computational geometric and simplex search techniques to determine the dimensional errors in manufactured components. The proposed hybrid algorithm works in two stages. First, it establishes a measurement coordinate system using basic computational geometric techniques such as convex hull and Voronoi diagrams. Next, the proposed hybrid algorithm modifies the initial measurement coordinate system by the simplex search technique. This helps to reduce the error between design and measurement coordinate systems. After determining the measurement coordinate system, the dimensional errors in the inspected components are estimated to verify the conformity of manufactured components to the design and tolerance specifications. In the present work, the proposed algorithm has been successfully implemented for inspecting the automobile chassis module. The required measurement data are obtained from a laser vision system developed for inspecting the automobile front chassis module that comprises the subframe and lower arm assembly. The measurement data from the subframe are used for establishing the measurement coordinate system. The dimensional errors in the lower arm are determined using the measurement coordinate system, established earlier. The details of the algorithm and the results obtained for the sample data are presented in this paper. The dimensional error values obtained using the proposed algorithms are compared to those obtained using the least-squares method.

자율 주행 용접 로봇을 위한 시각 센서 개발과 환경 모델링

Automation of welding process in shipyards is ultimately necessary, since the welding site is spatially enclosed by floors and girders, and therefore welding operators are exposed to hostile working conditions. To solve this problem, a welding mobile robot that can navigate autonomously within the enclosure has been developed. To achieve the welding task in the closed space, the robotic welding system needs a sensor system for the working environment recognition and the weld seam tracking, and a specially designed environment recognition strategy. In this paper, a three-dimensional laser vision system is developed based on the optical triangulation technology in order to provide robots with 3D work environmental map. Using this sensor system, a spatial filter based on neural network technology is designed for extracting the center of laser stripe, and evaluated in various situations. An environment modeling algorithm structure is proposed and tested, which is composed of the laser scanning module for 3D voxel modeling and the plane reconstruction module for mobile robot localization. Finally, an environmental recognition strategy for welding mobile robot is developed in order to recognize the work environments efficiently. The design of the sensor system, the algorithm for sensing the partially structured environment with plane segments, and the recognition strategy and tactics for sensing the work environment are described and discussed with a series of experiments in detail.

Laser vision system can be built into welding robot's controller

Laser vision system can be built into welding robot's controller

Three-dimensional inspection of ball grid array using laser vision system

An inspection process of the ball grid array (BGA) is proposed using a laser vision system which provides range image. This study suggests an inspection algorithm using the range images for evaluating the height of the solder ball, coplanarity and lead pitch, which are major factors in the BGA surface mounting technology. A feature-based algorithm was used in implementing region segmentation of range images. By deciding the BGA orientation using plane modeling, the errors of the range finding system were compensated and the reference of the height of the solder ball was found. Also, a method for measuring the height of the solder ball using free-form surface modeling was proposed. And, from the measured heights, the pitches and coplanarity were calculated.

Automatic visual inspection of surface mount solder joint defects

The ever increasing use of surface mount technology in printed circuit board assembly has considerably increased the importance of automated solder joint inspection. This paper documents our experience with the development of an experimental automated solder joint inspection system. Dominant solder joint defect classes are identified. Three-dimensional geometric models of these defects are created and used to test a non-parametric classification algorithm and optimal feature selection scheme. The classification algorithm and optimal feature selection scheme are then implemented on an experimental system using a laser line and vision system for solder joint data acquisition. The capability and limitations of this system are assessed through experimentation with actual solder joint defects.

Laser vision system to measure and track the attitude of a tether‐stabilized satellite system in a laboratory simulator

A bidimensional laboratory simulator to measure and control the attitude of a tether-stabilized platform for orbiting telescopes is presented and discussed. Yaw and libration angles are measured by plane tracking of the image of a laser spot, reflected on a screen by a mirror fixed to a floating platform. A multiple-reflection optical lever enables amplification of platform motion. The libration and yaw angles are related to the coordinates of the spot projected on the screen. Disturbances due to overall tether dynamics and telescope slewing are both reproduced and accounted for. Attitude control is achieved by moving the attachment point of the tether on the platform. Displacements are computed and commands are sent to a dc servo-motor via a PC. This measurement system allows platform libration ? and yaw ? angles to be measured to an accuracy of 0.06×10-3 rad; an accuracy of 0.4×10-3 rad in 10 s is reached in attitude control.

Determination of gas tungsten arc welding efficiencies

A combined experimental/computational technique for the estimation of gas tungsten arc welding (GTAW) efficiencies under quasi-steady conditions is presented. The instantaneous measurements of the weld pool length ahead of and behind the electrode are obtained from digitized free surface images, using a pulsed laser vision system. Measurements of the width and depth of the pool are obtained from weld sections using optical microscopy. Based on these measurements of the actual fusion boundary created by weldpool convection and other effects, a three-dimensional model outside the molten zone in the solid material is used to determine welding efficiency. Measurements and calculations are performed for a range of power inputs and torch speeds for both grooved and ungrooved, high-yield strength steel samples. Computed efficiencies are compared with those available in the literature.