Author Affiliations
1School of Electronic and Information Engineering, Liaoning Technical University, Huludao, Liaoning 125105, China2State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China3Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, Liaoning 110016, Chinashow less
Fig. 1. Binocular vision measurement system model
Fig. 2. Conversion from depth map to point cloud. (a) Depth map; (b) point cloud
Fig. 3. Schematic of rotation of 3D coordinate system. (a) Rotate around X axis; (b) rotate around Y axis; (c) rotate around Z axis
Fig. 4. Position representation of spatial point in world coordinate system
Fig. 5. Pose transformation of curved object
Fig. 6. Flow chart of the algorithm
Fig. 7. Experimental environment
Fig. 8. Experimental object. (a) Object 1; (b) object 2; (c) object 3; (d) object 4
Fig. 9. Selected target corner points
Fig. 10. Comparison of measurement errors of our algorithm and three monocular visual pose algorithms. (a) X-axis translation error; (b) Y-axis translation error; (c) Z-axis translation error; (d) rotation error around the X-axis; (e) rotation error around the Y-axis; (f) rotation error around the Z-axis
Fig. 11. Average error percentage of our algorithm and three monocular visual pose algorithms
Fig. 12. Comparison of measurement errors of our algorithm and two binocular visual pose algorithms. (a) X-axis translation error; (b) Y-axis translation error; (c) Z-axis translation error; (d) rotation error around the X-axis; (e) rotation error around the Y-axis; (f) rotation error around the Z-axis
Fig. 13. Average error percentage of our algorithm and two binocular visual pose algorithms
Data category | Translation /cm | Rotation angle /(°) |
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tx | ty | tz | ϕ | θ | ψ |
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Ground truth | 5.0000 | 4.5000 | 10.0000 | 0.0000 | 10.0000 | 10.0000 | Estimated value | 6.6207 | 4.0626 | 11.3933 | 4.2442 | 9.9221 | 10.3074 | Estimation error | 1.6207 | 0.4374 | 1.3933 | 4.2442 | 0.0779 | 0.3074 | Average error | 1.1505 | 1.5432 |
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Table 1. Estimation results of object 1 pose change
Data category | Translation /cm | Rotation angle /(°) |
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tx | ty | tz | ϕ | θ | ψ |
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Ground truth | 10.0000 | 4.5000 | 0.0000 | 5.0000 | 0.0000 | 0.0000 | Estimated value | 11.3664 | 4.8467 | 0.7567 | 4.0535 | 0.5914 | 0.7830 | Estimation error | 1.3664 | 0.3467 | 0.7567 | 0.9465 | 0.5914 | 0.7830 | Average error | 0.8233 | 0.7736 |
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Table 2. Estimation results of object 2 pose change
Data category | Translation /cm | Rotation angle /(°) |
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tx | ty | tz | ϕ | θ | ψ |
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Ground truth | 5.0000 | 0.0000 | 10.0000 | 0.0000 | 20.0000 | 0.0000 | Estimated value | 6.1803 | 0.1977 | 11.7300 | 4.7397 | 19.5883 | 1.8791 | Estimation error | 1.1803 | 0.1977 | 1.7300 | 4.7397 | 0.4117 | 1.8791 | Average error | 1.0360 | 2.3435 |
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Table 3. Estimation results of object 3 pose change
Data category | Translation /cm | Rotation angle /(°) |
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tx | ty | tz | ϕ | θ | ψ |
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Ground truth | 0.0000 | 0.0000 | 10.0000 | 5.0000 | 0.0000 | 0.0000 | Estimated value | 0.4850 | 0.0327 | 10.0533 | 3.3628 | 0.8692 | 2.2322 | Estimation error | 0.4850 | 0.0327 | 0.0533 | 1.6372 | 0.8692 | 2.2322 | Average error | 0.1903 | 1.5795 |
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Table 4. Estimation results of object 4 pose change
Object | Translation /cm | Rotation angle /(°) |
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1 | 1.1505 | 1.5432 | 2 | 0.8233 | 0.7736 | 3 | 1.0360 | 2.3435 | 4 | 0.1903 | 1.5795 |
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Table 5. Mean estimation error of each object
Algorithm | Running time /ms |
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otx | oty | otz | oϕ | oθ | oψ |
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COPE | 11.80 | 8.40 | 8.20 | 8.50 | 8.50 | 8.75 | ICP | 595.00 | 382.20 | 408.40 | 536.00 | 618.00 | 621.00 | Increased percentage /% | 98.02 | 97.80 | 97.99 | 98.41 | 98.62 | 98.59 | Average improved efficiency /% | 98.24 |
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Table 6. Comparison of calculation efficiency between COPE and ICP algorithm
Algorithm | Running time /ms |
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otx | oty | otz | oϕ | oθ | oψ |
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NDT | 210.00 | 305.00 | 429.20 | 614.00 | 570.00 | 640.00 | Increased percentage /% | 94.38 | 97.25 | 98.09 | 98.62 | 98.51 | 98.63 | Average improved efficiency /% | 97.58 |
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Table 7. Comparison of calculation efficiency between COPE and NDT algorithm