A review on visual servoing for underwater vehicle manipulation systems automatic control and case study

Huang, Hai; Bian, Xinyu; Cai, Fengchun; Li, Jiyong; Jiang, Tao; Zhang, Zhenkun; Sun, Chaoyu

doi:10.1016/j.oceaneng.2022.112065

Cited by 14 publications

(5 citation statements)

References 70 publications

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“…The concept of vision control seems to have been first proposed by Hill and Park in order to distinguish their approach from the earlier "blocks world" [96], and was first applied to the control of robotic arms. A good review of the application of vision-based servo control on robotic arms is given in [97].…”

Section: Vision-based Formation Controlmentioning

confidence: 99%

A Survey of An Intelligent Multi-Agent Formation Control

Chen¹,

Wang²,

Jin³

et al. 2023

Applied Sciences

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We present an overview of formation control for multi-agent systems. Multi-agent formation cooperation is important to accomplish assigned tasks more efficiently and safely compared to a single agent. For the way information flows between agents, we divide the available results into communication-based topologies as well as vision-based formation controls. Then, we summarize the problem formulation, discuss the differences, and review the latest results on formation control schemes. Lastly, we give research recommendations for multi-intelligent agent controls in a certain period in the future.

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Section: Vision-based Formation Controlmentioning

confidence: 99%

A Survey of An Intelligent Multi-Agent Formation Control

Chen¹,

Wang²,

Jin³

et al. 2023

Applied Sciences

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“…Visual perception is widely used in underwater vehicles [ 3 ]. For example, Huang et al focused on improving the operational precision of the end-effector system of underwater robots through visual servo control [ 4 ]. This research demonstrates that uncalibrated visual perception, guided by reinforcement learning, can direct the robot to perform repeatable actions.…”

Section: Introductionmentioning

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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“…Due to the limitations of underwater signal transmission, visual positioning is commonly used for operations in the local space. The most widely used visual servo method is the image-based visual servo (IBVS) [20,21], which does not require calculating the 3D information of the targets. Refs.…”

Section: Introductionmentioning

confidence: 99%

Reinforcement-Learning-Based Visual Servoing of Underwater Vehicle Dual-Manipulator System

Wang,

Gao

2024

JMSE

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As a substitute for human arms, underwater vehicle dual-manipulator systems (UVDMSs) have attracted the interest of global researchers. Visual servoing is an important tool for the positioning and tracking control of UVDMSs. In this paper, a reinforcement-learning-based adaptive control strategy for the UVDMS visual servo, considering the model uncertainties, is proposed. Initially, the kinematic control is designed by developing a hybrid visual servo approach using the information from multi-cameras. The command velocity of the whole system is produced through a task priority method. Then, the reinforcement-learning-based velocity tracking control is developed with a dynamic inversion approach. The hybrid visual servoing uses sensors equipped with UVDMSs while requiring fewer image features. Model uncertainties of the coupled nonlinear system are compensated by the actor–critic neural network for better control performances. Moreover, the stability analysis using the Lyapunov theory proves that the system error is ultimately uniformly bounded (UUB). At last, the simulation shows that the proposed control strategy performs well in the task of dynamical positioning.

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A review on visual servoing for underwater vehicle manipulation systems automatic control and case study

Cited by 14 publications

References 70 publications

A Survey of An Intelligent Multi-Agent Formation Control

A Survey of An Intelligent Multi-Agent Formation Control

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

Reinforcement-Learning-Based Visual Servoing of Underwater Vehicle Dual-Manipulator System

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