Infrared and Laser Engineering, Volume. 52, Issue 2, 20220367(2023)
Optimization and validation of coherent point drift for planar-array-based point cloud in space pose measurement
Figures & Tables(12)
Fig. 1. Diagram of the proposed adaptive CPD registration strategy for spatial planar-array-based point clouds
Fig. 2. (a) Variation of RMSE with the iterations ; (b) Convergence curve of RMSE under local minimum
Fig. 3. (a) Case 1: The platform rotates around the
Fig. 4. (a) Absolute simulation point cloud at a certain pose; (b) Degraded simulation point cloud with noise perturbation
Fig. 5. Registration results when the difference between the viewing angles of adjacent point cloud is 90 °under Case 1: (a) SAC+ ICP; (b) NDT + ICP; (c) PCA + ICP; (d) Proposed method
Fig. 6. Registration results when the viewing angle difference is 30° and 60° in Case 1: (a)-(d) are the results of SAC+ICP, NDT+ICP, PCA+ICP and the proposed method when the viewing angle difference is 30°. Similarly, (e)-(f) correspond to the 60° viewing angle difference
Fig. 7. Registration results when the distance between adjacent point cloud is 30 m under Case 2: (a) Initial position; (b) SAC + ICP; (c) NDT + ICP; (d) PCA + ICP; (e) Proposed method
Fig. 8. Continuous registration results for the point cloud with the distance difference between adjacent frames of 10 m and 20 m in Case 2: (a)-(b) corresponds to ∆
Fig. 9. Registration results under extreme strong noise : (a) - (d) are the results of SAC-ICP framework under different noise level; (e)-(h) is PCA + ICP; (i) - (l) Correspond to the registration method in this paper
Table 1. Evaluation of registration results when the viewing angles are 0° and 90° respectively in Case 1
View tableView in ArticleTable 1. Evaluation of registration results when the viewing angles are 0° and 90° respectively in Case 1
Method SAC+ICP NDT+ICP PCA+ICP Proposed Run time/s 2.03 1.85 1.72 2.10 LCP Rough 5.1% 15.1% 32.0% 69.2% Precise 18.0% 8.3% 63.6% RMSE Rough 0.651 0.504 0.131 0.106 Precise 0.174 0.474 0.102
Table 2. Evaluation of registration results in Case 2 when the detection distance is 90 m and 60 m respectively
View tableView in ArticleTable 2. Evaluation of registration results in Case 2 when the detection distance is 90 m and 60 m respectively
Method SAC+ICP NDT+ICP PCA+ICP Proposed Run time/s 2.62 2.42 2.28 2.54 LCP 58.8% 11.0% 34.5% 78.6% RMSE 0.105 0.459 0.146 0.114
Table 3. Evaluation of results when the distance is 90 m and 60 m respectively under strong noise disturbance in Case 2
View tableView in ArticleTable 3. Evaluation of results when the distance is 90 m and 60 m respectively under strong noise disturbance in Case 2
Method Evaluation $ \sigma =0.02,\tau =0.5 $ $ \sigma =0.02,\tau =0.8 $ $ \sigma =0.05,\tau =0.5 $ $ \sigma =0.05,\tau =0.8 $ SAC+ICP RMSE 0.154 0.110 0.133 0.143 LCP 25.4% 51.9% 25.0% 22.5% PCA+ICP RMSE 0.142 0.110 0.102 0.112 LCP 33.7% 52.0% 41.6% 38.7% Proposed RMSE 0.118 0.123 0.105 0.125 LCP 67.2% 69.1% 49.5% 48.4%
Tools
Get Citation
Copy Citation Text
Changsheng Tan, Genghua Huang, Fengxiang Wang, Wei Kong, Rong Shu. Optimization and validation of coherent point drift for planar-array-based point cloud in space pose measurement[J]. Infrared and Laser Engineering, 2023, 52(2): 20220367
Paper Information
Category: Photoelectric measurement
Received: May. 27, 2022
Accepted: --
Published Online: Mar. 13, 2023
The Author Email: Huang Genghua (genghuah@mail.sitp.ac.cn)
© Copyright 2018-2021 | Chinese Laser Press.
All Rights Reserved 沪ICP备15018463号-20