LiDAR-Based Three-Dimensional Modeling and Volume Calculation for Space Objects

Yanwei Hu; Jianjun Wang; Yuanyuan Fan; Yunpeng Lu; Chongyue Bai; Jiyun Zhang

doi:10.3788/CJL202047.0510001

Chinese Journal of Lasers, Volume. 47, Issue 5, 0510001(2020)

LiDAR-Based Three-Dimensional Modeling and Volume Calculation for Space Objects

Yanwei Hu¹, Jianjun Wang^1、*, Yuanyuan Fan², Yunpeng Lu¹, Chongyue Bai¹, and Jiyun Zhang¹

Author Affiliations

¹School of Mechanical Engineering, Shandong University of Technology, Zibo, Shandong 255049, China

²School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou, Gansu 730070, China

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Figures & Tables(14)

Fig. 1. Flow chart of point cloud processing

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Fig. 2. Schematic of coordinate rotation transformation. (a) First and second rotation; (b) third rotation

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Fig. 3. Experimental measurement site. (a) Collecting classroom data; (b) collecting corridor data; (c) point cloud visualization during acquisition

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Fig. 4. Experimental results and volume calculation results

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Fig. 5. Classroom point clouds under different k and α. (a) k=1, α=1.0; (b) k=1,α=1.4; (c) k=1, α=1.8; (d) k=4, α=1.0; (e) k=4, α=1.4; (f) k=4, α=1.8

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Fig. 6. Combination point clouds under different k and α. (a) k=1, α=1.0; (b) k=1, α=1.4; (c) k=1, α=1.8; (d) k=4, α=1.0; (e) k=4, α=1.4; (f) k=4, α=1.8

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Fig. 7. Classroom point clouds under different grid side length L_v. (a) 0.02 m; (b) 0.06 m; (c) 0.12 m; (d) 0.18 m

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Fig. 8. Combination point clouds under different grid side length L_v. (a) 0.02 m; (b) 0.06 m; (c) 0.12 m; (d) 0.18 m

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Fig. 9. Triangular mesh model of two experimental objects. (a) Classroom; (b) combination

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Table 1. Amount of point cloud of classroom after filtering under different k and α
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Table 1. Amount of point cloud of classroom after filtering under different k and α
k α
1.0 1.2 1.4 1.6 1.8
1 81258 84834 87910 90562 92898
2 82140 85722 88843 91511 93701
3 83948 87749 90542 92591 94067
4 85468 88909 91338 93015 94223

Table 2. Amount of point cloud of combination after filtering under different k and α
View table
Table 2. Amount of point cloud of combination after filtering under different k and α
k α
1.0 1.2 1.4 1.6 1.8
1 219644 230123 239980 247110 252330
2 223300 234091 242752 249090 253046
3 227909 237130 243769 248607 251782
4 230522 238643 244343 248378 251288

Table 3. Amounts of point cloud for classroom and combination under different grid side length L_v
View table
Table 3. Amounts of point cloud for classroom and combination under different grid side length L_v
L_v /m 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18
Classroom 92619 74240 49935 31349 21312 14772 11208 7929 6272
Combination 251568 208663 141828 89164 59113 41521 30633 23689 18145

Table 4. Classroom point cloud volume after filtering and down-sampling under different parameter combinationsm³

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Table 4. Classroom point cloud volume after filtering and down-sampling under different parameter combinationsm³

L_v /m	(k,α)
L_v /m	(1,1.0)	(1,1.2)	(1,1.4)	(2,1.0)	(2,1.2)	(2,1.4)
0.02	93.010	92.945	92.872	92.946	92.880	92.830
0.04	93.097	93.064	92.994	93.043	93.002	92.962
0.06	93.086	93.069	93.040	93.037	93.030	92.986
L_v /m	(k,α)
L_v /m	(3,1.0)	(3,1.2)	(3,1.4)	(4,1.0)	(4,1.2)	(4.1.4)
0.02	93.257	93.207	93.087	93.216	93.141	93.068
0.04	93.275	93.250	93.133	93.193	93.144	93.118
0.06	93.199	93.147	93.056	93.127	93.139	93.068

Table 5. Combination point cloud volume after filtering and down-sampling under different parameter combinationsm³

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Table 5. Combination point cloud volume after filtering and down-sampling under different parameter combinationsm³

L_v /m	(k,α)
L_v /m	(1,1.0)	(1,1.2)	(1,1.4)	(2,1.0)	(2,1.2)	(2,1.4)
0.02	226.880	226.663	226.759	226.826	226.668	226.559
0.04	226.933	226.903	226.744	226.860	226.700	226.701
0.06	226.771	226.712	226.700	226.826	226.755	226.595
L_v /m	(k,α)
L_v /m	(3,1.0)	(3,1.2)	(3,1.4)	(4,1.0)	(4,1.2)	(4.1.4)
0.02	227.119	227.051	226.919	226.978	227.016	226.932
0.04	227.200	227.150	227.061	226.956	227.089	227.083
0.06	227.035	226.954	226.852	226.987	226.985	226.907

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Yanwei Hu, Jianjun Wang, Yuanyuan Fan, Yunpeng Lu, Chongyue Bai, Jiyun Zhang. LiDAR-Based Three-Dimensional Modeling and Volume Calculation for Space Objects[J]. Chinese Journal of Lasers, 2020, 47(5): 0510001

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Paper Information

Category: remote sensing and sensor

Received: Oct. 23, 2019

Accepted: Dec. 19, 2019

Published Online: May. 12, 2020

The Author Email: Jianjun Wang (wangjianjun@sdut.edu.cn)

DOI:10.3788/CJL202047.0510001

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Amount of point cloud of classroom after filtering under different k and α

Table 1. Amount of point cloud of classroom after filtering under different k and α

Table 2. Amount of point cloud of combination after filtering under different k and α

Table 2. Amount of point cloud of combination after filtering under different k and α

Table 3. Amounts of point cloud for classroom and combination under different grid side length Lv

Table 3. Amounts of point cloud for classroom and combination under different grid side length Lv

Table 4. Classroom point cloud volume after filtering and down-sampling under different parameter combinationsm3

Table 4. Classroom point cloud volume after filtering and down-sampling under different parameter combinationsm3

Table 5. Combination point cloud volume after filtering and down-sampling under different parameter combinationsm3

Table 5. Combination point cloud volume after filtering and down-sampling under different parameter combinationsm3

Table 3. Amounts of point cloud for classroom and combination under different grid side length L_v

Table 3. Amounts of point cloud for classroom and combination under different grid side length L_v

Table 4. Classroom point cloud volume after filtering and down-sampling under different parameter combinationsm³

Table 4. Classroom point cloud volume after filtering and down-sampling under different parameter combinationsm³

Table 5. Combination point cloud volume after filtering and down-sampling under different parameter combinationsm³

Table 5. Combination point cloud volume after filtering and down-sampling under different parameter combinationsm³