Aluminum alloys have been widely utilized in automobiles, aircraft, building structures, and high-speed railways industries due to their excellent structural and mechanical properties. Surface oxide film removal prior to aluminum alloy welding and old paint removal prior to repainting aluminum alloy surfaces are critical factors in ensuring the welding quality and service life of aluminum alloy products. Because of its unique advantages, such as environmental protection and precision control, laser-controlled cleaning has great application potential as a surface cleaning technology in removing oxide films and paint layers on aluminum alloy surfaces. In this paper, the mechanism of laser cleaning of oxide films and paint layers on aluminum alloy is discussed. Furthermore, the impact of various processing parameters such as laser beam power, energy density, scanning speed, and so on is analyzed in detail. After laser cleaning, the corrosion resistance, welding performance, adhesive performance, and other properties of the aluminum alloy are optimized. This paper also discusses several real-time detection technologies for laser cleaning. A summary and the development trend are provided at the end of the paper.
This paper presents an optical flow-based novel technique to perceive the instant motion velocity of a smart wheelchair robot. The primary focus of this study is to determine the wheelchair's ego-motion using a displacement field in temporally consecutive image pairs. In contrast to most previous approaches for estimating velocity, the proposed strategy has two main innovations. Firstly, the proposed tilted overlooking camera set-up instead of conventional downward-looking camera and the corresponding ego-motion model is presented for compact indoor mobile robots. Secondly, by virtue of the graphic processing unit-accelerated TV-L 1 algorithm, which is coupled with motion priors-based pixel prediction, we are permitted to improve the accuracy and efficiency of the optical flow estimation significantly. In order to render our method more robust with respect to noise and outliers, we propose a quadratic motion model-based random sample consensus (RANSAC) refinement of flow fields. Advantages of our proposal are validated by real experimental results carried on our smart wheelchair platform and contrast evaluations conducted on Pioneer robot.
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