国家自然科学基金(61175084,61673042)
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Figure 1
Block diagram of the vision-based real-time obstacle perception method
Figure 2
(Color online) Samples in the data set
Figure 3
(Color online) Target detection and recognition results using YOLOv2
Figure 4
(Color online) 3D reconstruction based on binocular stereo vision
Figure 5
Obstacle extraction using information fusion method
Figure 6
Perception of the physical prototype. (a) Real-time detection result using YOLOv2 and KCF tracking algorithm; (b) point cloud for 3D environment reconstruction using binocular stereo vision
Figure 7
(Color online) Detection and tracking results for the physical object using the proposed algorithm. (a) Image at the 1st frame; (b) image at the 60th frame; (c) image at the 120th frame
| Center coordinate $X$ (m) | Center coordinate $Y$ (m) | Center coordinate $Z$ (m) | Width (m) | Height (m) | ||
| Group 1 | Real value | 0.000 | 0.000 | 1.500 | 0.370 | 0.370 |
| Measured value | $-$0.012 | 0.021 | 1.493 | 0.374 | 0.374 | |
| Error | $-$0.012 | 0.021 | $-$0.007 | 0.004 | 0.004 | |
| Group 2 | Real value | 0.000 | 0.400 | 1.980 | 0.370 | 0.370 |
| Measured value | 0.009 | 0.443 | 1.981 | 0.374 | 0.374 | |
| Error | 0.009 | 0.043 | 0.001 | 0.004 | 0.004 | |
| Group 3 | Real value | $-$0.400 | 0.400 | 2.500 | 0.370 | 0.370 |
| Measured value | $-$0.378 | 0.433 | 2.550 | 0.374 | 0.382 | |
| Error | 0.022 | 0.033 | 0.050 | 0.004 | 0.012 | |
| Group 4 | Real value | $-$0.400 | 0.400 | 3.000 | 0.370 | 0.370 |
| Measured value | $-$0.447 | 0.447 | 2.987 | 0.402 | 0.382 | |
| Error | $-$0.047 | 0.047 | 0.013 | 0.032 | 0.012 | |
| Group 5 | Real value | 0.000 | 0.400 | 4.000 | 0.370 | 0.370 |
| Measured value | 0.037 | 0.442 | 3.951 | 0.397 | 0.420 | |
| Error | 0.037 | 0.042 | 0.049 | 0.027 | 0.050 | |
| $X$-EM (cm) | $X$-SD (cm) | $Y$-EM (cm) | $Y$-SD (cm) | $Z$-EM (cm) | $Z$-SD (cm) | |
| Group 1 | 1.4 | 0.5 | 1.5 | 0.4 | 1.1 | 0.3 |
| Group 2 | 1.4 | 0.4 | 1.3 | 0.4 | 1.1 | 0.4 |
| Group 3 | 1.8 | 0.6 | 2.2 | 0.4 | 2.2 | 0.1 |
| Group 4 | 2.3 | 0.6 | 3.2 | 1.0 | 3.8 | 0.5 |
| Group 5 | 2.6 | 0.6 | 2.8 | 0.6 | 5.4 | 0.9 |
a$X/Y/Z$-EM represents $X/Y/Z$-axis position error mean value and $X/Y/Z$-SD represents $X/Y/Z$-axis standard deviation.
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