Hybrid Visual-Ranging Servoing for Positioning Based on Image and Measurement Features

Lin, Weiyang; Liu, Chenlu; Guo, Hao; Gao, Huijun

doi:10.1109/tcyb.2022.3160758

Cited by 9 publications

(3 citation statements)

References 27 publications

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“…f x and f y used to control the rotation motion around x-axis and y-axis. θ = 1 2 arctan 2μ 11 μ 20 −μ 02 is used to control rotational motion around the optical axis. We aim to choose a pair of features with significant decoupling characteristics, i.e., the features are only related to the rotational motion of the camera around the x-axis and y-axis, and are not affected by motion in other directions.…”

Section: Interaction Matrix and Image Featuresmentioning

confidence: 99%

“…To improve the interaction ability of robots with the environment or other intelligent agents in unstructured environments, robot visual servoing control technology has attracted extensive attention from many researchers and has been widely used in positioning tasks [1],aerospace [2],ultrasound image [3] and agricultural fields [4]. Visual servoing method can be divided into three categories [5]: 1) image-based visual servoing (IBVS), 2) position-based visual servoing (PBVS), and 3) hybrid visual servo control (HVS or 2.5-D VS).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Image moment-based visual positioning and robust tracking control of ultra-redundant manipulator

Li,

Zhou,

Zhu

et al. 2024

J Intell Robot Syst

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Image moment features can describe more general target patterns and have good decoupling properties. However, the image moment features that control the camera’s rotation motion around the x-axis and y-axis mainly depend on the target image itself. In this paper, the ultra-redundant manipulator visual positioning and robust tracking control method based on the image moments are advocated.First, six image moment features used to control camera motion around the x-axis and around the y-axis are proposed. And then, a novel method is proposed to use to select image features. For tracking a moving target, a kalman filter combined with adaptive fuzzy sliding mode control method is proposed to achieve tracking control of moving targets, which can estimate changes in image features caused by the target’s motion on-line and compensate for estimation errors. Finally, the experimental system based on Labview-RealTime system and ultra-redundant manipulator is used to verify the real-time performance and practicability of the algorithm. Experimental results are presented to illustrate the validity of the image features and tracking method.

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Section: Interaction Matrix and Image Featuresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Image moment-based visual positioning and robust tracking control of ultra-redundant manipulator

Li,

Zhou,

Zhu

et al. 2024

J Intell Robot Syst

View full text Add to dashboard Cite

show abstract

“…The uncontrollable contact force may cause damage to the robot or fragile touched objects such as mirrors [7] or human bodies [8]. In addition to safety, contact force control, such as force tracking, has a wide range of applications, especially when the visual serving is inaccessible or the position of the object being touched is biased towards contact operations such as grasping, manufacturing, assembly and tool wear [9][10][11][12].…”

Section: Introduction 1motivationsmentioning

confidence: 99%

Robot Manipulation Skills Transfer for Sim-to-Real in Unstructured Environments

Yin

et al. 2023

Electronics

Self Cite

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Robot force control that needs to be customized for the robot structure in unstructured environments with difficult-to-tune parameters guarantees robots’ compliance and safe human–robot interaction in an increasingly expanding work environment. Although reinforcement learning provides a new idea for the adaptive adjustment of these parameters, the policy often needs to be trained from scratch when used in new robotics, even in the same task. This paper proposes the episodic Natural Actor-Critic algorithm with action limits to improve robot admittance control and transfer motor skills between robots. The motion skills learned by simple simulated robots can be applied to complex real robots, reducing the difficulty of training and time consumption. The admittance control ensures the realizability and mobility of the robot’s compliance in all directions. At the same time, the reinforcement learning algorithm builds up the environment model and realizes the adaptive adjustment of the impedance parameters during the robot’s movement. In typical robot contact tasks, motor skills are trained in a robot with a simple structure in simulation and used for a robot with a complex structure in reality to perform the same task. The real robot’s performance in each task is similar to the simulated robot’s in the same environment, which verifies the method’s effectiveness.

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Research on monocular intelligent depth measurement method based on liquid bionic vision system

Gan

Hong

et al. 2023

Measurement

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Hybrid Visual-Ranging Servoing for Positioning Based on Image and Measurement Features

Cited by 9 publications

References 27 publications

Image moment-based visual positioning and robust tracking control of ultra-redundant manipulator

Image moment-based visual positioning and robust tracking control of ultra-redundant manipulator

Robot Manipulation Skills Transfer for Sim-to-Real in Unstructured Environments

Research on monocular intelligent depth measurement method based on liquid bionic vision system

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