Yin Guo

Sensor for In-Motion Continuous 3D Shape Measurement Based on Dual Line-Scan Cameras

The acquisition of three-dimensional surface data plays an increasingly important role in the industrial sector. Numerous 3D shape measurement techniques have been developed. However, there are still limitations and challenges in fast measurement of large-scale objects or high-speed moving objects. The innovative line scan technology opens up new potentialities owing to the ultra-high resolution and line rate. To this end, a sensor for in-motion continuous 3D shape measurement based on dual line-scan cameras is presented. In this paper, the principle and structure of the sensor are investigated. The image matching strategy is addressed and the matching error is analyzed. The sensor has been verified by experiments and high-quality results are obtained.

Rapid Global Calibration Technology for Hybrid Visual Inspection System

Vision-based methods for product quality inspection are playing an increasingly important role in modern industries for their good performance and high efficiency. A hybrid visual inspection system, which consists of an industrial robot with a flexible sensor and several stationary sensors, has been widely applied in mass production, especially in automobile manufacturing. In this paper, a rapid global calibration method for the hybrid visual inspection system is proposed. Global calibration of a flexible sensor is performed first based on the robot kinematic. Then, with the aid of the calibrated flexible sensor, stationary sensors are calibrated globally one by one based on homography. Only a standard sphere and an auxiliary target with a 2D planar pattern are applied during the system global calibration, and the calibration process can be easily re-performed during the system’s periodical maintenance. An error compensation method is proposed for the hybrid inspection system, and the final accuracy of the hybrid system is evaluated with the deviation and correlation coefficient between the measured results of the hybrid system and Coordinate Measuring Machine (CMM). An accuracy verification experiment shows that deviation of over 95% of featured points are less than ±0.3 mm, and the correlation coefficients of over 85% of points are larger than 0.7.

Stereo line-scan sensor calibration for 3D shape measurement

The stereo line-scan sensor opens up new potentialities for 3D measurement owing to the ultra-high resolution and acquisition rate. Calibration is a crucial key technology for a stereo line-scan sensor. This paper presents a precise calibration method for the stereo line-scan sensor. Several reference points are installed onto the sensors body as an intermediary. The calibration turns into a two-step process: calibrating the cameras in the laboratory prior to measurement and locating the sensor in an actual measurement field. A mobile apparatus that comprises a planar pattern and extra reference points is designed. By incorporating the apparatus in combination with an auxiliary instrument, an optimal calibration configuration is created by placing the apparatus into multiple positions. A robust algorithm is proposed to enhance the stability of the parameter estimation. The quality of the calibration method is experimentally tested, and the performance is further investigated. Experimental results demonstrate that the proposed method offers a practical solution to calibrate a stereo line-scan sensor for 3D shape measurement.

A Novel Semi-Supervised Feature Extraction Method and Its Application in Automotive Assembly Fault Diagnosis Based on Vision Sensor Data

The fault diagnosis of dimensional variation plays an essential role in the production of an automotive body. However, it is difficult to identify faults based on small labeled sample data using traditional supervised learning methods. The present study proposed a novel feature extraction method named, semi-supervised complete kernel Fisher discriminant (SS-CKFDA), and a new fault diagnosis flow for automotive assembly was introduced based on this method. SS-CKFDA is a combination of traditional complete kernel Fisher discriminant (CKFDA) and semi-supervised learning. It adjusts the Fisher criterion with the data global structure extracted from large unlabeled samples. When the number of labeled samples is small, the global structure that exists in the measured data can effectively improve the extraction effects of the projected vector. The experimental results on Tennessee Eastman Process (TEP) data demonstrated that the proposed method can improve diagnostic performance, when compared to other Fisher discriminant algorithms. Finally, the experimental results on the optical coordinate data proves that the method can be applied in the automotive assembly process, and achieve a better performance.

A new single-station wMPS measurement method with distance measurement

Multi-task and real-time measurement of relative displacement is widely needed in the present industrial field. Existing measuring methods require complex preparation and data processing, or are unable meet the requirement of automation, multi-task and real-time. The instruments used to measure absolute coordinates are inefficiency because of the measured target is relative displacement. A new single-station wMPS (Workspace Measuring Position System) measurement method combined distance measurement is presented in this paper. It learns from measuring principle of total station, measures angle based on rotating scanning laser plane measuring method, and measures distance based on optoelectronic scanning multi-angle intersection location principle, uses the angle-length resection measuring method, builds a new mathematical model to measure the relative displacement of the target. The result of experiment proves that it increases measuring efficiency and achieves multi-task and real-time measurement of relative displacement.

A structured light sensor measuring method based on wMPS global controlling

In large-scale three-dimensional (3D) coordinates measurement, to solve the problem of structured light sensor’s measurement data from different measurement stations unifying to the global coordinate system, a method based on workshop Measuring Position System (wMPS) global controlling is researched to concentrate the structured light sensor’s measurement data to the global coordinate system automatically. According to the measurement principle, two calibration methods are proposed to calibrate the structural parameters based on a standard ball, one is transferring stations based on common points and the other is fitting ball equation. Finally, a platform for experiment is built to verify the two calibration methods. Experimental results show that the average measurement error on 10 points is 0.127 mm according to the laser tracker of the first method and the other average error is 0.101 mm, both the two calibration methods have a high precision to meet the demands of large-scale 3D coordinates measurement.

A stereo line-scan system for 3D shape measurement of fast-moving objects

With outstanding features of high resolution and high acquisition rate, line-scan imaging holds great potentials for high-speed applications. This paper presents a stereo line-scan system for 3D shape measurement of fast moving objects. The principle and key technologies are addressed. The system setup and 3D imaging model are introduced first and the stereo matching scheme and calibration approach are described subsequently. The system is verified by experiments. The results demonstrate the validity and accuracy of the proposed system.

Monocular-Based 6-Degree of Freedom Pose Estimation Technology for Robotic Intelligent Grasping Systems

Industrial robots are expected to undertake ever more advanced tasks in the modern manufacturing industry, such as intelligent grasping, in which robots should be capable of recognizing the position and orientation of a part before grasping it. In this paper, a monocular-based 6-degree of freedom (DOF) pose estimation technology to enable robots to grasp large-size parts at informal poses is proposed. A camera was mounted on the robot end-flange and oriented to measure several featured points on the part before the robot moved to grasp it. In order to estimate the part pose, a nonlinear optimization model based on the camera object space collinearity error in different poses is established, and the initial iteration value is estimated with the differential transformation. Measuring poses of the camera are optimized based on uncertainty analysis. Also, the principle of the robotic intelligent grasping system was developed, with which the robot could adjust its pose to grasp the part. In experimental tests, the part poses estimated with the method described in this paper were compared with those produced by a laser tracker, and results show the RMS angle and position error are about 0.0228° and 0.4603 mm. Robotic intelligent grasping tests were also successfully performed in the experiments.

Relationship between Coordinate Transformation Uncertainty and Arrangement of Common Reference Points in Large-Scale Metrology

Large-scale coordinate measurement frequently involves unifying coordinate frames of individual measurement systems by aligning two sets of common reference points, which is called coordinate transformation. During this transformation process, some uncertainty is introduced into the final measurement results from common points. This paper studies the relationship between this introduced uncertainty and common points in order to minimize it. First, an uncertainty estimation model of coordinate transformation is developed to quantify the introduced uncertainty. Then the relationship between the introduced uncertainty and the arrangement of the common points is simulationally and experimentally investigated and some feasible and efficient arrangements are proposed in view of minimizing it.

Photoelectric scanning-based method for positioning omnidirectional automatic guided vehicle

Abstract. Automatic guided vehicle (AGV) as a kind of mobile robot has been widely used in many applications. For better adapting to the complex working environment, more and more AGVs are designed to be omnidirectional by being equipped with Mecanum wheels for increasing their flexibility and maneuverability. However, as the AGV with this kind of wheels suffers from the position errors mainly because of the frequent slipping property, how to measure its position accurately in real time is an extremely important issue. Among the ways of achieving it, the photoelectric scanning methodology based on angle measurement is efficient. Hence, we propose a feasible method to ameliorate the positioning process, which mainly integrates four photoelectric receivers and one laser transmitter. To verify the practicality and accuracy, actual experiments and computer simulations have been conducted. In the simulation, the theoretical positioning error is less than 0.28 mm in a 10  m×10  m space. In the actual experiment, the performances about the stability, accuracy, and dynamic capability of this method were inspected. It demonstrates that the system works well and the performance of the position measurement is high enough to fulfill the mainstream tasks.