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This paper aims to use 3D laser sensors to collect high‐density data that are required for defect detection and localization at high‐production rates in manufacturing facilities.

The high‐speed sensors use Ethernet communications to transport large amounts of data and resolve any synchronization issues.

Modern laser sensor technology provides the ability to detect and quantify defects in high‐volume manufacturing, wherever defects are located. Laser line sensors provide high speed, high‐density data for full surface inspection. Synchronization and communications issues are simplified by the FireSync™ platform, making system integration straightforward, and maximizing reliability.

This paper provides detailed 3D data at high speed and uses multiple (binocular) scanners to overcome problems of occlusion.

This paper aims to propose a hand–eye calibration method of arc welding robot and laser vision sensor by using semidefinite programming (SDP).

The conversion relationship between the pixel coordinate system and laser plane coordinate system is established on the basis of the mathematical model of three-dimensional measurement of laser vision sensor. In addition, the conversion relationship between the arc welding robot coordinate system and the laser vision sensor measurement coordinate system is also established on the basis of the hand–eye calibration model. The ordinary least square (OLS) is used to calculate the rotation matrix, and the SDP is used to identify the direction vectors of the rotation matrix to ensure their orthogonality.

The feasibility identification can reduce the calibration error, and ensure the orthogonality of the calibration results. More accurate calibration results can be obtained by combining OLS + SDP.

A set of advanced calibration methods is systematically established, which includes parameters calibration of laser vision sensor and hand–eye calibration of robots and sensors. For the hand–eye calibration, the physics feasibility problem of rotating matrix is creatively put forward, and is solved through SDP algorithm. High-precision calibration results provide a good foundation for future research on seam tracking.

Existing calibration methods mainly focus on the camera laser-plane calibration of a single laser-line length, which is not convenient and cannot guarantee the consistency of the results when several three-dimensional (3D) scanners are involved. Thus, this study aims to provide a unified step for different laser-line length calibration requirements for laser profile measurement (LPM) systems.

3D LPM is the process of converting physical objects into 3D digital models, wherein camera laser-plane calibration is critical for ensuring system precision. However, conventional calibration methods for 3D LPM typically use a calibration target to calibrate the system for a single laser-line length, which needs multiple calibration patterns and makes the procedure complicated. In this paper, a unified calibration method was proposed to automatically calibrate the camera laser-plane parameters for the LPM systems with different laser-line lengths. The authors designed an elaborate planar calibration target with different-sized rings that mounted on a motorized linear platform to calculate the laser-plane parameters of the LPM systems. Then, the camera coordinates of the control points are obtained using the intersection line between the laser line and the planar target. With a new proposed error correction model, the errors caused by hardware assembly can be corrected. To validate the proposed method, three LPM devices with different laser-line lengths are used to verify the proposed system. Experimental results show that the proposed method can calibrate the LPM systems with different laser-line lengths conveniently with standard steps.

The repeatability and accuracy of the proposed calibration prototypes were evaluated with high-precision workpieces. The experiments have shown that the proposed method is highly adaptive and can automatically calibrate the LPM system with different laser-line lengths with high accuracy.

In the repeatability experiments, there were errors in the measured heights of the test workpieces, and this is because the laser emitter had the best working distance and laser-line length.

By using this proposed method and device, the calibration of the 3D scanning laser device can be done in an automatic way.

The calibration efficiency of a laser camera device is increased.

The authors proposed a unified calibration method for LPM systems with different laser-line lengths that consist of a motorized linear joint and a calibration target with elaborately designed ring patterns; the authors realized the automatic parameter calibration.

The purpose of this study is solving the hand–eye calibration issue for line structured light vision sensor. Only after hand–eye calibration the sensor measurement data can be applied to robot system.

In this paper, the hand–eye calibration methods are studied, respectively, for eye-in-hand and eye-to-hand. Firstly, the coordinates of the target point in robot system are obtained by tool centre point (TCP), then the robot is controlled to make the sensor measure the target point in multiple poses and the measurement data and pose data are obtained; finally, the sum of squared calibration errors is minimized by the least square method. Furthermore, the missing vector in the process of solving the transformation matrix is obtained by vector operation, and the complete matrix is obtained.

On this basis, the sensor measurement data can be easily and accurately converted to the robot coordinate system by matrix operation.

This method has no special requirement for robot pose control, and its calibration process is fast and efficient, with high precision and has practical popularized value.

This paper aims to propose a set of six-axis robot arm welding seam tracking experiment platform based on Halcon machine vision library to resolve the curve seam tracking issue.

Robot-based and image coordinate systems are converted based on the mathematical model of the three-dimensional measurement of structured light vision and conversion relations between robot-based and camera coordinate systems. An object tracking algorithm via weighted local cosine similarity is adopted to detect the seam feature points to prevent effectively the interference from arc and spatter. This algorithm models the target state variable and corresponding observation vector within the Bayes framework and finds the optimal region with highest similarity to the image-selected modules using cosine similarity.

The paper tests the approach and the experimental results show that using metal inert-gas (MIG) welding with maximum welding current of 200A can achieve real-time accurate curve seam tracking under strong arc light and splash. Minimal distance between laser stripe and welding molten pool can reach 15 mm, and sensor sampling frequency can reach 50 Hz.

Designing a set of six-axis robot arm welding seam tracking experiment platform with a system of structured light sensor based on Halcon machine vision library; and adding an object tracking algorithm to seam tracking system to detect image feature points. By this technology, this system can track the curve seam while welding.

This paper aims to propose a robotic automation system for processing special-shaped thin-walled workpieces, which includes a measurement part and a processing part.

In the measurement part, to efficiently and accurately realize the three-dimensional camera hand-eye calibration based on a large amount of measurement data, this paper improves the traditional probabilistic method. To solve the problem of time-consuming in the extraction of point cloud features, this paper proposes a point cloud feature extraction method based on seed points. In the processing part, the authors design a new type of chamfering tool. During the process, the robot adopts admittance control to perform compensation according to the feedback of four sensors mounted on the tool.

Experiments show that the proposed system can make the tool smoothly fit the chamfered edge during processing and the machined chamfer meets the processing requirements of 0.5 × 0.5 to 0.9 × 0.9 mm².

The proposed design and approach can be applied on many types of special-shaped thin-walled parts. This will give a new solution for the automation integration problem in aerospace manufacturing.

A novel robotic automation system for processing special-shaped thin-walled workpieces is proposed and a new type of chamfering tool is designed. Furthermore, a more accurate probabilistic hand-eye calibration method and a more efficient point cloud extraction method are proposed, which are suitable for this system when comparing with the traditional methods.

Steel beam welding at a construction site is challenging due to the increasing thickness of steel members in today's buildings. In order to achieve high quality welding and resolve the problem caused by the shortage of skilled welders, robotic systems are in high demand. We have proposed a practical robotic system for steel beam welding, specifically designed for working on H‐shaped column structures that are known to be the most difficult structures for automation.