Improved Iterative Closest Contour Point Matching Navigation Algorithm Based on Geomagnetic Vector

Ren, Yuan; Wang, Lihui; Lin, Kunjie; Ma, Hongwei; Ma, Mingzhu

doi:10.3390/electronics11050796

Cited by 3 publications

(3 citation statements)

References 15 publications

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“…Further, ICCP has high matching accuracy when the initial error is small, but it often has poor matching accuracy when the initial error is large. [5][6][7] ICCP has been improved by many scholars. Liu et al 8 proposed a real-time ICCP with an optimized matching sequence length (OMSL-ICCP), which can obtain the current optimal matching sequence length through searching the current measurements to reduce matching error.…”

Section: Introductionmentioning

confidence: 99%

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Underwater terrain-matching algorithm based on improved iterative closest contour point algorithm

Wang,

Liu,

Ben

et al. 2024

Measurement and Control

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Although an autonomous underwater vehicle (AUV) is noted for its good autonomy, concealment and anti-interference ability, errors in its inertial navigation system (INS) inevitably increase over time, leading to positional failure during long-term voyages. Terrain-assisted navigation can help the INS to correct its position. The traditional iterative closest contour point (ICCP) achieves high matching accuracy when the initial position error of the INS is small, but is prone to mismatching when the initial error is large. This study combines ICCP with particle swarm optimization (PSO) to overcome this problem. First, the global optimization ability of PSO is improved by changing the acceleration factor and introducing an artificial bee colony (ABC) onlooker bee greedy search (ABC- ωAPSO). Second, the Euclidean distance of ICCP is replaced by the Mahalanobis distance to abate the influence of system error on the matching accuracy. Finally, the initial position error is reduced by rough matching using the ABC- ωAPSO, which has global optimization capability. Next, fine matching is performed by ICCP. This two-step process resolves the sensitivity problem of ICCP to the initial position error. The experimental results revealed a good matching effect after the double-matching procedure. When the initial INS errors were 0.55′ to the east and 0.55′ to the north, the matching error was reduced to 89.3 m, suggesting that the approach can realize autonomous passive navigation of AUVs.

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Section: Introductionmentioning

confidence: 99%

“…Further, ICCP has high matching accuracy when the initial error is small, but it often has poor matching accuracy when the initial error is large. 5–7…”

Section: Introductionmentioning

confidence: 99%

Underwater terrain-matching algorithm based on improved iterative closest contour point algorithm

Wang,

Liu,

Ben

et al. 2024

Measurement and Control

View full text Add to dashboard Cite

show abstract

“…Over the past few years, a lot of research results on multiview point cloud data alignment have been put forward at home and abroad. For example, (ICP) algorithm proposed by BESL et al [18] in 1992 is a classical point cloud alignment algorithm, and the ICP algorithm and its improvements [19][20][21] have also become the most widely used alignment algorithms in the industry. However, the results of such algorithms are dependent on the relative positional relationships of the point cloud data.…”

Section: Introductionmentioning

confidence: 99%

Research on Object Panoramic 3D Point Cloud Reconstruction System Based on Structure From Motion

et al. 2022

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3D reconstruction is the transformation of real objects into mathematical models. By using 3D models, we can observe the shape and measure the parameters, and help us to analyze the properties of objects. For the problems of incompleteness and inefficiency in the reconstruction of object 3D point clouds, a fast and automated system for panoramic 3D point cloud reconstruction of objects was proposed. First, we designed an automatic platform, which could acquire RGB image sequences of objects in two directions. Then we adopted the Structure From Motion (SFM) algorithm to generate point clouds. For the problem of different scales of point clouds, we obtained the scaling by calculating the length ratio of the axes of the oriented bounding box, and scaled the point clouds to a uniform scale. In addition, markers were placed around the object and used to acquire the rotation matrix of the object point cloud in two directions. Finally, we verified the point cloud models of different objects generated by the system, and found that the relative error didn't exceed 6.67%. According to the results, the system proposed could reconstruct the panoramic 3D point cloud of the object better and provide a reference for related research.

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Lane Level Positioning Method for Unmanned Driving Based on Inertial System and Vector Map Information Fusion Applicable to GNSS Denied Environments

Dai

Liang

et al. 2023

Drones

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With the development of vehicle sensors, unmanned driving has become a research hotspot. Positioning is also considered to be one of the most challenging directions in this field. Aiming at the poor positioning accuracy of vehicles under GNSS denied environments, a lane-level positioning method based on inertial system and vector map information fusion is proposed. A dead reckoning model based on optical fiber IMU and odometer is established, and its positioning error is regarded as a priori information. Furthermore, a map matching model based on HMM is built up. Three validation experiments are carried out and experimental results show that the positioning error can be reduced to less than 30 cm when driving for about 7 min, which proves the effectiveness of the proposed method. Our work may provide a reference for the further improvement of positioning for unmanned driving under GNSS denied environments.

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Improved Iterative Closest Contour Point Matching Navigation Algorithm Based on Geomagnetic Vector

Cited by 3 publications

References 15 publications

Underwater terrain-matching algorithm based on improved iterative closest contour point algorithm

Underwater terrain-matching algorithm based on improved iterative closest contour point algorithm

Research on Object Panoramic 3D Point Cloud Reconstruction System Based on Structure From Motion

Lane Level Positioning Method for Unmanned Driving Based on Inertial System and Vector Map Information Fusion Applicable to GNSS Denied Environments

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