Acta Photonica Sinica, Volume. 53, Issue 4, 0415001(2024)
Global Low Bias Visual/inertial/weak-positional-aided Fusion Navigation System
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Fig. 3. ArUco target coordinate system definition and coordinate transformation between camera and ArUco target
Fig. 6. Laser point cloud map generation and trajectory truth value generation
Fig. 7. Navigation result trajectories of each method under three scenarios
Fig. 9. Examples of ArUco target distribution can be seen in the path and ArUco target detection
Fig. 10. Navigation trajectory comparison with or without ArUco assistance
Table 1. System hardware parameter
View tableView in ArticleTable 1. System hardware parameter
Type of sensor Picture Model Frequency/Hz Specification Gray camera 
DALSA M1930 20 Resolution： 960×600 IMU 
Xsens Mti-680G 400 Noise： 0.002°/s Hz-0.5 and 0.01 ms-2 Hz-0.5 GNSS 
u-blox ZED-F9P-01B 10 Horizontal pos accuracy （PVT）： 1.5 m CEP Ultrasonic tag 
Marvelmind Super-Beacon 0.1~7 Accuracy： 1%~3% （Base station distance） LiDAR 
Velodyne VLP16 10 FoV： 360°×30° Accuracy： ±3 cm@100 m
Table 2. Error test results under different experimental conditions
View tableView in ArticleTable 2. Error test results under different experimental conditions
Sequence Evaluation index Error results （mean/median/RMSE） Ours VINS-Mono ORB-SLAM3 Indoor RPE/%↓ 0.837/0.669/1.044 1.401/1.317/1.573 4.193/4.496/4.543 ATE/m↓ 0.619/0.556/0.740 3.359/3.587/3.523 3.041/2.759/3.653 Daytime in-outdoor RPE/%↓ 2.622/2.177/3.234 3.039/2.382/3.786 7.091/7.148/7.426 ATE/m↓ 2.813/2.627/3.325 5.017/4.867/5.435 8.861/8.262/10.32 Nighttime in-outdoor RPE/%↓ 2.028/1.743/2.278 5.451/3.323/7.387 10.32/9.899/11.61 ATE/m↓ 2.988/3.108/3.495 9.313/8.983/10.77 12.55/10.62/15.02
Table 3. Error test results with or without ArUco assistance
View tableView in ArticleTable 3. Error test results with or without ArUco assistance
Evaluation index Error results （mean/median/RMSE） VIO+ArUco （ours） VIO RPE/%↓ 3.518/3.182/4.023 3.645/3.394/4.106 ATE/m↓ 2.917/2.935/3.045 6.412/7.132/6.683
Table 4. The single processing run time of this method in different scenarios
View tableView in ArticleTable 4. The single processing run time of this method in different scenarios
Indoor Daytime outdoor Nighttime outdoor Daytime in-outdoor Nighttime in-outdoor Average time spent/ms 29.04 23.51 27.39 23.54 27.95
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Yufeng XU, Yuanzhi LIU, Minghui QIN, Hui ZHAO, Wei TAO. Global Low Bias Visual/inertial/weak-positional-aided Fusion Navigation System[J]. Acta Photonica Sinica, 2024, 53(4): 0415001
Paper Information
Category: Machine Vision
Received: Oct. 26, 2023
Accepted: Dec. 13, 2023
Published Online: May. 15, 2024
The Author Email: Wei TAO (taowei@sjtu.edu.cn)
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