Localization Method for Underwater Robot Swarms Based on Enhanced Visual Markers

Wei, Qingbo; Yang, Yi; Zhou, Xingqun; Fan, Chuanzhi; Zheng, Quan; Hu, Zhiqiang

doi:10.3390/electronics12234882

Cited by 4 publications

(1 citation statement)

References 44 publications

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“…In natural underwater scenarios, features are sparse. The proposed feature matching method uses low-cost chessboard markers, which are easier to make and obtain compared to specially designed three-dimensional markers [ 34 , 35 ]. The proposed marker-assisted feature-enhanced matching method avoids time-consuming and laborious underwater scene setting and provides the feature point pairs needed for image stitching in a cost-effective manner.…”

Section: Binocular Visual Field Stitching For Fish-like Vision Systemmentioning

confidence: 99%

A Fish-like Binocular Vision System for Underwater Perception of Robotic Fish

Tong,

Wu,

Wang

et al. 2024

Biomimetics

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Biological fish exhibit a remarkably broad-spectrum visual perception capability. Inspired by the eye arrangement of biological fish, we design a fish-like binocular vision system, thereby endowing underwater bionic robots with an exceptionally broad visual perception capacity. Firstly, based on the design principles of binocular visual field overlap and tangency to streamlined shapes, a fish-like vision system is developed for underwater robots, enabling wide-field underwater perception without a waterproof cover. Secondly, addressing the significant distortion and parallax of the vision system, a visual field stitching algorithm is proposed to merge the binocular fields of view and obtain a complete perception image. Thirdly, an orientation alignment method is proposed that draws scales for yaw and pitch angles in the stitched images to provide a reference for the orientation of objects of interest within the field of view. Finally, underwater experiments evaluate the perception capabilities of the fish-like vision system, confirming the effectiveness of the visual field stitching algorithm and the orientation alignment method. The results show that the constructed vision system, when used underwater, achieves a horizontal field of view of 306.56°. The conducted work advances the visual perception capabilities of underwater robots and presents a novel approach to and insight for fish-inspired visual systems.

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Section: Binocular Visual Field Stitching For Fish-like Vision Systemmentioning

confidence: 99%

A Fish-like Binocular Vision System for Underwater Perception of Robotic Fish

Tong,

Wu,

Wang

et al. 2024

Biomimetics

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A Visual Perception Algorithm for AUV Dynamic Docking Based on Variable Markers

Xing,

Zhang,

Liu

et al. 2024

OCEANS 2024 - Halifax

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Enhancing Inter-AUV Perception: Adaptive 6-DOF Pose Estimation with Synthetic Images for AUV Swarm Sensing

Wei,

Yang,

Zhou

et al. 2024

Drones

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The capabilities of AUV mutual perception and localization are crucial for the development of AUV swarm systems. We propose the AUV6D model, a synthetic image-based approach to enhance inter-AUV perception through 6D pose estimation. Due to the challenge of acquiring accurate 6D pose data, a dataset of simulated underwater images with precise pose labels was generated using Unity3D. Mask-CycleGAN technology was introduced to transform these simulated images into realistic synthetic images, addressing the scarcity of available underwater data. Furthermore, the Color Intermediate Domain Mapping strategy is proposed to ensure alignment across different image styles at pixel and feature levels, enhancing the adaptability of the pose estimation model. Additionally, the Salient Keypoint Vector Voting Mechanism was developed to improve the accuracy and robustness of underwater pose estimation, enabling precise localization even in the presence of occlusions. The experimental results demonstrated that our AUV6D model achieved millimeter-level localization precision and pose estimation errors within five degrees, showing exceptional performance in complex underwater environments. Navigation experiments with two AUVs further verified the model’s reliability for mutual 6D pose estimation. This research provides substantial technical support for more complex and precise collaborative operations for AUV swarms in the future.

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Localization Method for Underwater Robot Swarms Based on Enhanced Visual Markers

Cited by 4 publications

References 44 publications

A Fish-like Binocular Vision System for Underwater Perception of Robotic Fish

A Fish-like Binocular Vision System for Underwater Perception of Robotic Fish

A Visual Perception Algorithm for AUV Dynamic Docking Based on Variable Markers

Enhancing Inter-AUV Perception: Adaptive 6-DOF Pose Estimation with Synthetic Images for AUV Swarm Sensing

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