Filtering algorithm of line structured light for long-distance obstacle detection

Since unmanned ground vehicles often encounter concave and convex obstacles in wild ground, a filtering algorithm using line structured light to detect these long distance obstacles is proposed. For the line structured light image, a ranked-order based adaptively extremum median （RAEM） filter algorithm on salt and pepper noise is presented. In the algorithm, firstly effective points and noise points in a filtering window are differentiated; then the gray values of noise points are replaced by the medium of gray values of the effective pixels, with the efficient points＇ gray values unchanged; in the end this algorithm is proved to be efficient by experiments. Experimental resuits demonstrate that the image blur, resulting into proposed algorithm can remove noise points effectively and minimize the protecting the edge information as much as possible.

High Curvature Stripe Profile Extraction Algorithm of Line Structured Light Measuring System

In the line structured light measuring system, the accuracy of the process of laser stripe directly affects the measurement results. Therefore, the extraction algorithm for the laser stripe, especially the surface with high reflection and high curvature, is very important. The imaging principle of line structured light, the light intensity distribution law of laser stripe and the extraction algorithm have been studied, and a stripe profile extraction method based on real light intensity distribution has been proposed. In this algorithm, fast region of interest extraction, stripe width estimation, and adaptive filtering on the striped image are performed. Then the energy center of the stripe at the sub-pixel level is extracted. Finally, the low-quality center points are eliminated, and the context information is used to recover the missing central points. Simulated images generated based on the imaging principle of line structured light and real experimental images were used to evaluate the accuracy and repeatability of the proposed method. The results show that the method behaves excellently at the edges of high-curvature stripes;the maximum error is only 1.6 pixels, which is 1/10 of the classic Steger algorithm;the experiment repeatability is only 8.8 μm, which is 2.7 times that of the Steger method. Therefore, the proposed method improves the accuracy of object contour extraction, and it is especially suitable for contour detection of objects with high curvature.

Development of an In-Situ Laser Machining System Using a Three-Dimensional Galvanometer Scanner

In this study, a three-dimensional (3D) in-situ laser machining system integrating laser measurement and machining was built using a 3D galvanometer scanner equipped with a side-axis industrial camera. A line structured light measurement model based on a galvanometer scanner was proposed to obtain the 3D information of the workpiece. A height calibration method was proposed to further ensure measurement accuracy, so as to achieve accurate laser focusing. In-situ machining software was developed to realize time-saving and labor-saving 3D laser processing. The feasibility and practicability of this in-situ laser machining system were verified using specific cases. In comparison with the conventional line structured light measurement method, the proposed methods do not require light plane calibration, and do not need additional motion axes for 3D reconstruction;thus they provide technical and cost advantages. The insitu laser machining system realizes a simple operation process by integrating measurement and machining,which greatly reduces labor and time costs.