Optimized Combination of Spray Painting Trajectory on 3D Entities

Chen, Wei; Wang, Xinxin; Líu, Hao; Tang, Yang; Liu, Junjie

doi:10.3390/electronics8010074

Cited by 14 publications

(10 citation statements)

References 14 publications

(11 reference statements)

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“…When a UVMS robot hovers over an underwater object, it will cause vibration or even instability of the UVMS body. e distance between the mass center position of the UVMS and the ZMP position is set as the performance index as in equation (27). In this paper, performance metrics are minimized along with redundancy analysis.…”

Section: Underwater Manipulator Redundancymentioning

confidence: 99%

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Grasping Control of a UVMS Based on Fusion Visual Image Enhancement

Chen

Wang

Zhang

et al. 2020

Mathematical Problems in Engineering

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The Underwater Vehicle Manipulator System (UVMS) is an essential equipment for underwater operations. However, it is difficult to control due to the constrained problems of weak illumination, multidisturbance, and large inertia in the underwater environment. After the UVMS mathematical model based on water flow disturbance is established, fusion image enhancement algorithm based on Retinex theory is proposed to achieve fine perception of the target. The control method based on redundant resolution algorithm is adopted to establish the anti-interference controller of the manipulator, which can compensate the internal and external uncertain interference. Finally, stable underwater operation is realized. The target ranging method is used to solve the angle of each joint of the manipulator to complete the tracking and grasping of the target. Underwater experiments show that the algorithm can improve the clarity of underwater images, ensure the accuracy of robot capture, and optimize the UVMS control performance.

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Section: Underwater Manipulator Redundancymentioning

confidence: 99%

“…e effectiveness of fusion algorithm in detail processing is confirmed by the improvement of information entropy. In the future, we will study 3D feature extraction and positioning technology of underwater targets based on point cloud data [26,27].…”

Section: Image Enhancement Contrast Experimentmentioning

confidence: 99%

Grasping Control of a UVMS Based on Fusion Visual Image Enhancement

Chen

Wang

Zhang

et al. 2020

Mathematical Problems in Engineering

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“…In order to improve the control accuracy of the two-joint manipulator, a fuzzy neural network control algorithm, the fuzzy neural network (FNN) is constructed to optimize the conventional sliding mode control because of the chattering phenomenon in the conventional sliding-mode control [27][28][29][30]. The system consists of an input layer, an adaptive fuzzy rule layer, a rule layer, and an output layer.…”

Section: Sliding-mode Control Based On Complex Fuzzy Neural Networkmentioning

confidence: 99%

Picking Robot Visual Servo Control Based on Modified Fuzzy Neural Network Sliding Mode Algorithms

Chen

Liu

et al. 2019

Electronics

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Through an analysis of the kinematics and dynamics relations between the target positioning of manipulator joint angles of an apple-picking robot, the sliding-mode control (SMC) method is introduced into robot servo control according to the characteristics of servo control. However, the biggest problem of the sliding-mode variable structure control is chattering, and the speed, inertia, acceleration, switching surface, and other factors are also considered when approaching the sliding die surface. Meanwhile, neural network has the characteristics of approaching non-linear function and not depending on the mechanism model of the system. Therefore, the fuzzy neural network control algorithm can effectively solve the chattering problem caused by the variable structure of the sliding mode and improve the dynamic and static performances of the control system. The comparison experiment is carried out through the application of the PID algorithm, the sliding mode control algorithm, and the improved fuzzy neural network sliding mode control algorithm on the picking robot system in the laboratory environment. The result verified that the intelligent algorithm can reduce the complexity of parameter adjustments and improve the control accuracy to a certain extent.

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“…This special issue also includes papers that describe new and interesting applications of the visual servoing systems such as the ones described in [4] or [5]. In [4], a visual servoing system is applied to an apple-picking robot.…”

Section: The Present Issuementioning

confidence: 99%