Hyunki Lee

Sensor fusion of phase measuring profilometry and stereo vision for three-dimensional inspection of electronic components assembled on printed circuit boards

Automatic optical inspection (AOI) for printed circuit board (PCB) assembly plays a very important role in modern electronics manufacturing industries. Well-developed inspection machines in each assembly process are required to ensure the manufacturing quality of the electronics products. However, generally almost all AOI machines are based on 2D image-analysis technology. In this paper, a 3D-measurement-method-based AOI system is proposed consisting of a phase shifting profilometer and a stereo vision system for assembled electronic components on a PCB after component mounting and the reflow process. In this system information from two visual systems is fused to extend the shape measurement range limited by 2pi phase ambiguity of the phase shifting profilometer, and finally to maintain fine measurement resolution and high accuracy of the phase shifting profilometer with the measurement range extended by the stereo vision. The main purpose is to overcome the low inspection reliability problem of 2D-based inspection machines by using 3D information of components. The 3D shape measurement results on PCB-mounted electronic components are shown and compared with results from contact and noncontact 3D measuring machines. Based on a series of experiments, the usefulness of the proposed sensor system and its fusion technique are discussed and analyzed in detail.

An active trinocular vision system for sensing mobile robot navigation environments

Intelligent autonomous mobile robots must be able to sense and recognize 3D indoor space where they live or work. In this paper, we propose a new 3D sensing system using the laser structured lighting method, because of its robustness on the nature of the navigation environment and the easy extraction of feature information of interest The proposed active trinocular vision system is composed of a flexible multi-stripe laser projector and two cameras arranged with a triangular shape. Based on the virtual camera concept and the trinocular epipolar constraints, the matching pairs of line features in two real camera images are established, and 3D information from one-shot image can be extracted on the patterned scene. Especially, for robust line feature matching, we propose a new correspondence matching algorithms based on line grouping and probabilistic voting. Finally, a series of experimental tests is performed to show its efficiency and accuracy.

Visual gyroscope: Integration of visual information with gyroscope for attitude measurement of mobile platform

In this paper, fusion of visual and inertial information is proposed for attitude measurement of remotely-operated mobile robots. The primary objective is to eliminate the drift error of the inertial sensors using visual information for exact and fast sensing of attitude. By this fusion each output is not only combined together but also helps the other yield better result. The environment is assumed unknown and corner features are utilized for rotation matrix calculation, for corners are better extracted in nature scene than lines. The measured information is to be used for stabilizing the image sent to the operator and for stabilizing the robot body itself in bumpy terrain. In the paper, the fusion algorithm based on Kalman filter is utilized, and its performance is evaluated by experiment. For the experiment, high performance camera is used with low-quality gyro sensors. The experimental results show that the vision algorithm well tracks the attitude change of the camera, and by fusing that with gyro sensor output, we could get high rate angle measurement without drift error.

STEREO MOIRE TECHNIQUE: A NOVEL 3-D MEASUREMENT METHOD USING A STEREO CAMERA AND A DIGITAL PATTERN PROJECTOR

This article deals with a novel 3-D sensor system that employs a measurement technique called the Stereo Moiré technique. The general Moiré method, which is well known for fast and accurate 3-D measurement, has suffered from an inherent limitation in that it cannot measure the absolute 3-D depth due to 2π ambiguity caused by regularity of fringe. In this article, to overcome this 2π ambiguity and obtain the exact depth value effectively, a novel method is proposed. The measurement system consists of a digital pattern projector and two cameras, which can indirectly detect two phase information on the fringe patterns projected onto an objects surface. These two phase values are different due to the difference in camera position. However, the depth values obtained at two different phase information must be identical because the two cameras look at the same point on the object being measured. To verify the efficiency and accuracy of the proposed method, a series of experimental tests was performed. Through the experiments, it is shown that the proposed method can effectively overcome the 2π ambiguity of the typical Moiré technique, and obtain the absolute depth value of the 3-D scene geometric information with satisfactory accuracy.

Evolution of grain structure of as-deposited Cr thin films with deposition temperature

Abstract The growth of Cr thin films prepared by DC-magnetron sputter deposition was investigated by measuring the evolution of the grain size distribution and by computing the film growth using Monte Carlo simulation. The variation of grain size distribution with the deposition temperature is analyzed in terms of the film growth mechanisms.

A new 3D sensing method based on stereo PMP technique for mobile robots

Intelligent autonomous mobile robots must be able to sense and recognize 3D environment for navigation and task execution where they live or work. To achieve this, a variety of techniques have been developed for the determination of the 3D geometric information such as stereo vision, laser structured light, laser range finder and so on. However, these methods have several limitations such as susceptibility to noise, low resolution, measurement error in 3D scene. In this paper to overcome these problems we introduce a new sensing method based upon stereo vision methodology which utilizes not only intensity information but also phase information. The novelty of this suggested method comes from the fact that it uses the stereo phase information from the PMP technique together with intensity information captured by stereo image. To verify the efficiency and accuracy of the proposed method, a series of experimental tests is performed. The results show that it greatly enhances correspondence matching performance and measurement resolution.

A Sensor Fusion Method for Mobile Robot Navigation

An important and challenging research issue associated with mobile robot navigation is simultaneous localization and map building (SLAM), which means that the mobile robot could estimate its poses in the environment without external information, and simultaneously align the local maps. Various kinds of methods such as odometry measurement, landmark matching, laser range image matching and scale invariant feature (SIFT) based algorithm have already been proposed to solve this kind of research problems, but they suffer from inevitable drawbacks. For example, range image matching may suffer from local minimum problem and thus can not get a good location estimation sometimes, and SIFT algorithm can not work if few SIFT intensity features exist in the environment. Furthermore, the map built by laser range image matching is not good for localization when the robot returns to the prior map built by itself, and the map built by SIFT could not be used for obstacle avoidance and next view generation. To solve these problems, in this paper, we propose a sensor fusion method, which makes use of Dempster Shafer algorithm to fuse both of the laser range information and SIFT features information for SLAM. Through a series of experiments, the proposed method is tested and evaluated

A New 3D Sensor System for Mobile Robots Based on Moire and Stereo Vision Technique

Intelligent autonomous mobile robots must be able to sense and recognize 3D environment for navigation and task execution, where they live or work. To achieve this, a variety of techniques have been developed for the determination of the 3D scene geometric information such as stereo vision, laser structured light, laser range finder and so on. But these methods have many limitations such as susceptibility to noise, low speed in 3D scene etc. To overcome these limitations we introduce a new sensing algorithm, which is based on the moire technique and stereo vision. To verify the efficiency and accuracy of our algorithm, a series of experimental tests is performed

Three-dimensional sensing methodology combining stereo vision and phase-measuring profilometry based on dynamic programming

Abstract. Phase measuring profilometry and moiré methodology have been widely applied to the three-dimensional shape measurement of target objects, because of their high measuring speed and accuracy. However, these methods suffer from inherent limitations called a correspondence problem, or 2π-ambiguity problem. Although a kind of sensing method to combine well-known stereo vision and phase measuring profilometry (PMP) technique simultaneously has been developed to overcome this problem, it still requires definite improvement for sensing speed and measurement accuracy. We propose a dynamic programming-based stereo PMP method to acquire more reliable depth information and in a relatively small time period. The proposed method efficiently fuses information from two stereo sensors in terms of phase and intensity simultaneously based on a newly defined cost function of dynamic programming. In addition, the important parameters are analyzed at the view point of the 2π-ambiguity problem and measurement accuracy. To analyze the influence of important hardware and software parameters related to the measurement performance and to verify its efficiency, accuracy, and sensing speed, a series of experimental tests were performed with various objects and sensor configurations.

Active imaging system with variable viewing direction and position for 3D shape measurement in occluded region

Nowadays, a number of 3D shape measurement methods have been developed such as stereo vision, laser structured light, and Phase Measuring Profilometry (PMP). They have many problems such as correspondence problem, 2π-ambiguity and occlusion problem. Among them, occlusion problem is common problem for 3D shape measurement and well known as difficult to solve. To solve this problem, we suggest a new sensing system based on optical scanning system and movable mirror system, which can change the viewing angle without changing of field-of-view (FOV), and can do the FOV with maintaining the viewing angle. The performance of our system is checked by simulation and a series of real experiments.