Knowledge based recognition of harbor target

Zhu, Bing; Jin-zong, LI; Cheng, Aijun

doi:10.1016/s1004-4132(07)60011-5

Cited by 7 publications

(2 citation statements)

References 3 publications

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“…A rough first alignment is made and then the Iterative Closest Point (ICP) algorithm is used to estimate a transformation that fully aligns the correspondences in both clouds. Model and knowledge based approaches are also presented by the likes of Qi Chen et al [9] and Zhu Bing et al [10], utilizing satellite provided images to identify a possible harbor location with computer vision algorithms.…”

Section: Related Workmentioning

confidence: 99%

An Hierarchical Architecture for Docking Autonomous Surface Vehicles

Leite

Silva

Matos

et al. 2019

2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

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Autonomous Surface Vehicles (ASVs) provide the ideal platform to further explore the many opportunities in the cargo shipping industry, by making it more profitable and safer. This paper presents an architecture for the autonomous docking operation, formed by two stages: a maneuver module and, a situational awareness system to detect a mooring facility where an ASV can safely dock. Information retrieved from a 3D LIDAR, IMU and GPS are combined to extract the geometric features of the floating platform and to estimate the relative positioning and orientation of the moor to the ASV. Then, the maneuver module plans a trajectory to a specific position and guarantees that the ASV will not collide with the mooring facility. The approach presented in this paper was validated in distinct environmental and weather conditions such as tidal waves and wind. The results demonstrate the ability of the proposed architecture for detecting the docking platform and safely conduct the navigation towards it, achieving errors up to 0.107 m in position and 6.58 • in orientation.

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Section: Related Workmentioning

confidence: 99%

An Hierarchical Architecture for Docking Autonomous Surface Vehicles

Leite

Silva

Matos

et al. 2019

2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

View full text Add to dashboard Cite

show abstract

“…the algorithm based on parallel lines [2] would be invalid in the case that parallel lines are not detected or not exist and the contour-based algorithm [3] recognized port by convexo concave elements would be not in force any more if the convexo concave elements are not identified, and so on [4]. So, global feature-based detection algorithm is studied in some papers [5][6][7]. Closure is the inherent and more stable structure of port target.…”

Section: Introductionmentioning

confidence: 99%

Object-Oriented Port Detection Based on Mean Shift Segmentation

Yang

Qin

2010

2010 International Conference on Electrical and Control Engineering

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In this paper, we propose a new method for port detection using remote sensing image. This technique is a combination of image segmentation and object-oriented detection. We use mean shift method to initially segment the remote sensing image. Based on the initial segmentation map we build the spatial adjacency relation of the regions. Significant department has been observed in object-oriented detection. Generally, ports have inherent characteristic of half close region of seawater. Convex polygon created by centers of land region along the coastline. The land region is controlled within a certain range. Port detection is implemented according to water areas within the convex polygon. The advantages of this method are the robustness and its affine invariance with respect to translation, scaling, rotation and skewing. The effectiveness of this algorithm is demonstrated using two remote sensing images.

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The framework of target recognition in the field of remote sensing image based on knowledge

Wang

2009

2009 Chinese Control and Decision Conference

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Knowledge based recognition of harbor target

Cited by 7 publications

References 3 publications

An Hierarchical Architecture for Docking Autonomous Surface Vehicles

An Hierarchical Architecture for Docking Autonomous Surface Vehicles

Object-Oriented Port Detection Based on Mean Shift Segmentation

The framework of target recognition in the field of remote sensing image based on knowledge

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