Name
Title | ||
|---|---|---|
Multiview Point Cloud Registration Based on Minimum Potential Energy for Free-Form Blade Measurement |
Abstract | ||
|---|---|---|
Point cloud registration is an essential step for free-form blade reconstruction in industrial measurement. Nonetheless, measuring defects of the 3-D acquisition system unavoidably result in noisy and incomplete point cloud data, which renders efficient and accurate registration challenging. In this article, we propose a novel global registration method that is based on the minimum potential energy (MPE) method to address these problems. The basic strategy is that the objective function is defined as the MPE optimization function of the physical registration system. The function distributes more weight to the majority of inlier points and less weight to the noise and outliers, which essentially reduces the influence of perturbations in the mathematical formulation. We decompose the solution into a globally optimal approximation procedure and a fine registration process with the trimmed iterative closest point algorithm to boost convergence. The approximation procedure consists of two main steps. First, according to the construction of the force traction operator, we can simply compute the position of the potential energy minimum. Second, to find the MPE point, we propose a new theory that employs two flags to observe the status of the registration procedure. We demonstrate the performance of the proposed algorithm on four types of blades. The proposed method outperforms the other global methods in terms of both accuracy and noise resistance. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TIM.2022.3169559 | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT |
Keywords | DocType | Volume |
Blades, Point cloud compression, Three-dimensional displays, Potential energy, Pollution measurement, Noise measurement, Energy measurement, Free-form blade measurement, global robust method, measuring defects, minimum energy registration, turbine blade | Journal | 71 |
ISSN | Citations | PageRank |
0018-9456 | 0 | 0.34 |
References | Authors | |
0 | 8 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zijie Wu | 1 | 0 | 0.34 |
| Yaonan Wang | 2 | 1150 | 118.92 |
| Yang Mo | 3 | 0 | 0.34 |
| Qing Zhu | 4 | 0 | 0.34 |
| He Xie | 5 | 0 | 0.34 |
| Haotian Wu | 6 | 0 | 1.01 |
| Mingtao Feng | 7 | 9 | 3.53 |
| A. Mian | 8 | 1679 | 84.89 |