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A multi-laser sensors-based measurement instrument is proposed for the measurement of geometry errors of a differential body and quality evaluation. This paper aims to discuss the aforementioned idea.

First, the differential body is set on a rotation platform before measuring. Then one laser sensor called as “primary sensor”, is installed on the intern of the differential body. The spherical surface and four holes on the differential body are sampled by the primary sensor when the rotation platform rotates one revolution. Another sensor called as “secondary sensor”, is installed above to sample the external cylinder surface and the planar surface on the top of the differential body, and the external cylinder surface and the planar surface are high in manufacturing precision, which are used as datum surfaces to compute the errors caused by the motion of the rotation platform. Finally, the sampled points from the primary sensor are compensated to improve the measurement accuracy.

A multi-laser sensors-based measurement instrument is proposed for the measurement of geometry errors of a differential body. Based on the characteristics of the measurement data, a gradient image-based method is proposed to distinguish different objects from laser measurement data. A case study is presented to validate the measurement principle and data processing approach.

The study investigates the possibility of correction of sensor data by the measurement results of multiple sensors to improving measurement accuracy. The proposed technique enables the error analysis and compensation by the geometric correlation relationship of various features on the measurand.

The proposed error compensation principle by using multiple sensors proved to be useful for the design of new measurement device for special part inspection. The proposed approach to describe the measuring data by image also is proved to be useful to simplify the measurement data processing.

Cylindrical components are common in industry assembly areas. It is necessary to obtain their precise positions and orientations for their assemblies. But some measurement approaches relying on measuring targets are not allowed, as they may not meet the efficiency requirement of on-line measurement or may cause surface damages to the components. Thus, this paper aims to provide a precise on-line non-target scanning method based on 3D vision.

First, a laser profile sensor is used to acquire point cloud of the side surface of the measured cylindrical component. Then a composite process is conducted to estimate the pose and position of the axis. Aiming at this purpose, two fitting approaches, i.e., axis fitting and generatrix fitting, are tried respectively to estimate the pose parameters from the point cloud.

The results of Monte Carlo simulations demonstrate that neither the axis fitting nor the generatrix fitting could solely obtain the needed accuracy and precisions roundly. Thus, a new synthesis method is presented. And the results of prototype experiments validate the excellent accuracy and precision of the synthesis method.

This proposed new synthesis method combines the advantages of both the above fitting methods and can be easily integrated into the assembly line to guide the automation assembly process of the cylindrical components precisely.

Describes a rugged, high speed structured laser light triangulation‐based vision‐type sensor, with real‐time image processor, along with some actual applications. High speed is essential for a low dynamic error at the laser welding speed (10m/minute). Square butt joint, frequently used in welding, requires high sensor resolution and a complementary detection technique based on the reflected light intensity. Shows some welding techniques, based on the joint geometry measurements; illustrates capabilities of the vision‐based sensor.

Although a laser profile sensor (LPS) can be used to measure dimensions, the “shadow region” generally degrades the accuracy and precision of width measurements. The accuracy and precision of such measurements should be improved.

In this paper, the authors propose herein a technique that combines high dynamic range (HDR) imaging with logistic fitting. First, a HDR image is composed of several images acquired with different exposure times, which augments the grayscale of the object profile and significantly reduces overexposure. Next, the profile is fit to a logistic function, which provides accurate and precise edge coordinates. Finally, given the edge coordinates, the object width is calculated.

To verify the stability of this logistic algorithm, the authors simulate different noise conditions and different degrees of incomplete edge data. In addition, the progressiveness of the algorithm is demonstrated by comparing the results with those of other algorithms and with the height measurement. Furthermore, the suitability of the system is verified experimentally.

Because of the limitation of the condition of laboratory, in the experimental section, this paper cannot represent perfectly the industrial situation. It makes this section limited in demonstration.

In this paper, the results show that the measurement accuracy and precision of the width is improved and exceeds that of the height measurement. The proposed HDR imaging method with logistic fitting may be applied to LPS width measurements, which should significantly aid the development of LPSs.

This paper presents a method for extracting the geometric primitives of a circle in a three-dimensional space from a discrete point cloud data set obtained by a laser stripe sensor. This paper aims to first establish a reference frame for the robotic drilling process by detecting the position and orientation of a reference hole on structural parts in a pre-drilling step, and second, to perform quality inspection of the hole in a post-drilling step.

The method is divided into the following steps: a plane is initially fitted on the data by evaluating the principle component analysis using singular value decomposition; the data points or measurements are then rotated around an arbitrary axis using the Rodrigues’ rotation formula such that the normal direction of the estimated plane and the z-axis direction is parallel; the Delaunay triangulation is constructed on the point cloud and the confidence interval is estimated for segmenting the data set located at the circular boundary; and finally, a circular profile is fitted on the extracted set and transformed back to the original position.

The geometric estimation of the circle in three-dimensional space constitutes of the position of the center, the diameter and the orientation, which is represented by the normal vector of the plane that the circle lives in. The method is applied on both simulated data set with the addition of several noise levels and experimental data sets. The main purpose of both the tests is to quantify the accuracy of the estimated diameter. The results show good accuracy (mean relative error < 1 per cent) and high robustness to noise.

The proposed method is applied here to estimate the geometric primitives of only one circle (the reference hole). If multiple circles are needed, an addition clustering procedure is required to cluster the segmented data into multiple data sets. Each data set represents a circle. Also, the method does not operate efficiently on a sparse data sets. Dense data are required to cover the hole (at least ten scans to cover the hole diameter).

Researchers and practitioners can integrate this method with several robotic manufacturing applications where high accuracy is required. The extracted position and orientation of the hole are used to minimize the positioning and alignment errors between the mounted tool tip and the workpiece.

The method introduces data analytics for estimating the geometric primitives in the robotic drilling application. The main advantage of the proposed method is to register the top surface of the workpiece with respect to robot base frame with a high accuracy. An accurate workpiece registration is extremely necessary in the lateral direction (identifying where to drill), as well as in the vertical direction (identifying how far to drill).

This paper reviews the Weldex exhibition held at the NEC in Birmingham in November 2003. Highlights of the show included VirtualArc from ABB, which is able to predict weld conditions using physics of the arc, the hybrid MSG‐laser welding process from Cloos and a new spot weld‐specific Motoman robot. Several manufacturers displayed off‐the‐shelf “plug and weld” cells including Cloos, Fanuc and Autotech Robotics. Servo controlled guns were also featured by Motoman Robotics and Rexroth Bosch. The latter also promoted its ultrasonic weld monitoring systems that integrate with Rexroth's medium frequency welding systems for high quality assurance spot welding. Finally, a new laser seam tracker from Micro Epsilon is described.