A Vision-Based Robotic Laser Welding System for Insulated Mugs with Fuzzy Seam Tracking Control

Fang, Zaojun; Weng, Wenwu; Zhang, Chi; Yang, Guilin

doi:10.3390/sym11111385

Cited by 11 publications

(5 citation statements)

References 20 publications

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“…Fang et al [10] designed a vision-based seam tracking system of a robotic laser welding for stainless steel insulated mugs. Firstly, the vision sensor scanned the weld seam and feature points were collected.…”

Section: Introductionmentioning

confidence: 99%

A Novel 3D Complex Welding Seam Tracking Method in Symmetrical Robotic MAG Welding Process Using a Laser Vision Sensing

Zhang

Huang

et al. 2023

Symmetry

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The welding seam tracking operation ensures that the welding torch of the welding robot can go with the welding seam during the whole symmetrical robotic welding procession. To achieve three-dimensional complex welding seams tracking, a four-step welding seam tracking system is suggested based on segmented scanning, combined filtering, feature-point extraction, and welding path planning. From using the laser sensor installed at the end of welding robot, the welding seam data was continuously collected in multiple segments by segmented scanning. For the purpose of improving seam tracking accuracy, a combined filtering technique was used to correct the data to reduce the effects of burrs, data distortion, and noise on the surface of the weldment. Then, the feature points were collected so that the coordinate system will be calibrated to identify the welding points. Finally, a spatial welding path was obtained by welding path planning. Experimental investigations of the two-dimensional (2D) symmetrical S-shaped and three-dimensional (3D) curved welding seams were conducted. The obtained results demonstrate the proposed method can form a complete welding path. The average errors of the two weldments are about 0.296 mm and 0.292 mm, respectively. This shows that the proposed tracking method is effective and can provide a reference for the research of high-precision seam tracking and automatic welding.

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Section: Introductionmentioning

confidence: 99%

A Novel 3D Complex Welding Seam Tracking Method in Symmetrical Robotic MAG Welding Process Using a Laser Vision Sensing

Zhang

Huang

et al. 2023

Symmetry

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“…It can stabilize a physically constrained mobile robot. In [21], a vision system is applied for the laser welding system of insulated mugs. The authors propose a vision-based seam tracking system using a fuzzy logic control method.…”

Section: Introductionmentioning

confidence: 99%

Vision/Position Hybrid Control for a Hexa Robot Using Bacterial Foraging Optimization in Real-time Pose Adjustment

Huynh

Kuo

2020

Symmetry

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This paper presents a novel architecture of the vision/position hybrid control for a Hexa parallel robot. The 3D vision system is combined with the Proportional-Integral-Derivative (PID) position controller to form a two-level closed-loop controller of the robot. The 3D vision system measures the pose of the end-effector after the PID control. The measurement of the 3D vision system is used as a feedback of the second closed-loop control. The 3D vision system has a simple structure using two fixed symmetric cameras at the top of the robot and four planar colored markers on the surface of the end-effector. The 3D vision system detects and reconstructs the 3D coordinates of colored markers. Based on the distance and coplanarity constraints of the colored markers, the optimization problem is modeled for the real-time adjustment, which is implemented during the operation of the robot to minimize the measurement error of the 3D vision system due to both the initial calibration of the stereo camera and the external noise affecting image processing. The bacterial foraging optimization is appropriately configured to solve the optimization problem. The experiment is performed on a specific Hexa parallel robot to assess the effectiveness and feasibility of the proposed real-time adjustment using the bacterial foraging optimization. The experimental result shows that it has high accuracy and fast computation time although the experiment is conducted on a laptop with an average hardware configuration. An experimental comparison of the performance between the proposed method and another control method is also implemented. The results show the superiority and application potential of the proposed method.

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“…In recent years, with the rapid development of computer, automation and artificial intelligence, robot technology has drawn tremendous attractions, since robots can be widely used for human-robot collaboration [1], robotic laser welding [2], robotic precision farming [3], and medical treatment [4]. As an important carrier of artificial intelligence, how to design intelligent robots has become an active research subject.…”

Section: Introductionmentioning

confidence: 99%

“…In order to verify the working stability of the robot, a supermarket simulation environment is built, and two working modes of automatic commodity procurement and replenishment are verified. (2) We develop a small-scale image dataset containing 12 supermarket commodities, and compare three different methods for commodities detection and recognition with the designed supermarket service robot. Experiment results demonstrate the effectiveness of the proposed method.…”

Section: Introductionmentioning

confidence: 99%

Designing a Supermarket Service Robot Based on Deep Convolutional Neural Networks

et al. 2020

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In order to save people’s shopping time and reduce labor cost of supermarket operations, this paper proposes to design a supermarket service robot based on deep convolutional neural networks (DCNNs). Firstly, according to the shopping environment and needs of supermarket, the hardware and software structure of supermarket service robot is designed. The robot uses a robot operating system (ROS) middleware on Raspberry PI as a control kernel to implement wireless communication with customers and staff. So as to move flexibly, the omnidirectional wheels symmetrically installed under the robot chassis are adopted for tracking. The robot uses an infrared detection module to detect whether there are commodities in the warehouse or shelves or not, thereby grasping and placing commodities accurately. Secondly, the recently-developed single shot multibox detector (SSD), as a typical DCNN model, is employed to detect and identify objects. Finally, in order to verify robot performance, a supermarket environment is designed to simulate real-world scenario for experiments. Experimental results show that the designed supermarket service robot can automatically complete the procurement and replenishment of commodities well and present promising performance on commodity detection and recognition tasks.

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A Vision-Based Robotic Laser Welding System for Insulated Mugs with Fuzzy Seam Tracking Control

Cited by 11 publications

References 20 publications

A Novel 3D Complex Welding Seam Tracking Method in Symmetrical Robotic MAG Welding Process Using a Laser Vision Sensing

A Novel 3D Complex Welding Seam Tracking Method in Symmetrical Robotic MAG Welding Process Using a Laser Vision Sensing

Vision/Position Hybrid Control for a Hexa Robot Using Bacterial Foraging Optimization in Real-time Pose Adjustment

Designing a Supermarket Service Robot Based on Deep Convolutional Neural Networks

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