Search

Underwater welding robots play a crucial role in addressing challenges such as low efficiency, suboptimal performance, and high risks associated with underwater welding operations. These robots face a dual challenge encompassing both hardware deployment and software algorithms. Recent years have seen significant interest in humanoid robots and artificial intelligence (AI) technologies, which hold promise as breakthrough solutions for advancing underwater welding capabilities. Firstly, this review delves into the hardware platforms envisioned for future underwater humanoid welding robots (UHWR), encompassing both underwater apparatus and terrestrial support equipment. Secondly, it provides an extensive overview of AI applications in underwater welding scenarios, particularly focusing on their implementation in UHWR. This includes detailed discussions on multi-sensor calibration, vision-based three-dimensional (3D) reconstruction, extraction of weld features, decision-making for weld repairs, robot trajectory planning, and motion planning for dual-arm robots. Through comparative analysis within the text, it becomes evident that AI significantly enhances capabilities such as underwater multi-sensor calibration, vision-based 3D reconstruction, and weld feature extraction. Moreover, AI shows substantial potential in tasks like underwater image enhancement, decision-making processes, robot trajectory planning, and dual-arm robot motion planning. Looking ahead, the development trajectory for AI in UHWR emphasizes multifunctional models, edge computing in compact models, and advanced decision-making technologies in expansive models. [ABSTRACT FROM AUTHOR]

The main goal of this paper was to connect two controllers of the older generation into one robotic cell, then software implement their synchronized work on servicing and welding certain objects. For this purpose, two controllers manufactured by Yaskawa Motoman were used with the associated manipulators. The hardware solution involved connecting the controllers via General I/O circuit board, where the output of one controller is connected to the input of another and vice versa. The software solution involved parallel programming of two robots for synchronized operation on a common task. During programming, it was necessary to create macro jobs that implemented repetitive actions, such as calling and waiting for robots, grabbing and releasing objects, as well as the actions of starting and stopping the program. The conclusion of presented research is that the robotic cell, formed by two robots that are not intended for synchronization, meets the requirements that until now could only be solved with robots of the newer generation. Proposed solution was confirmed by experimental verification.

Initial weld point (IWP) guiding technology is an essential component of intelligent welding. To address the issues associated with current IWP guiding, a precise guiding technology based on binocular vision and structured light vision is proposed. Firstly, binocular cameras can identify the initial weld region (IWR) through the improved Yolov8 object detection algorithm. After the IWP identification and binocular ranging, the point is approximately located. Then, the position of the structured light camera relative to the approximate IWP is determined by structured light planes. After identifying the weld feature points and boundary points, the camera posture is rectified to extract precise weld depth information, enabling the precise locating of the IWP. Finally, to verify the accuracy of visual locating, the welding torch is guided to the IWP, and the difference between guiding position and actual position is compared. Experimental results show that the proposed method can precisely locate the IWP, meeting subsequent welding requirements. [ABSTRACT FROM AUTHOR]

The objective of the work is the design and simulation of a flexible manufacturing structure with two robots, integrated in a welding application, using the Roboguide software. FANUC ROBOGUIDE is a robot simulator that simulates both the movement of the robots and the commands from the designed application, significantly reducing the time needed to create new motion configurations.The possibility to import the CAD models of the components, of the fixing devices and of the final effectors of the robots integrated into the designed application, allows the creation and evaluation of various structures. Automatic program generation simplifies manual programming operations. ROBOGUIDE allows pre-programming of robots before they are installed in a cell, as well as visualization and confirmation of robot trajectories before downloading the programs to the real robot.

The rapid development of the construction industry has highlighted the urgent need for enhanced construction efficiency and safety, propelling the development of construction robots to ensure sustainable and intelligent industry advancement. Welding robots, in particular, hold significant promise for application in steel structure construction. However, harsh construction environments, variable construction structures, and complex construction conditions present critical technical challenges for weld position, path, and quality for welding robots. This paper aims to provide a focused review of the key technical difficulties faced by welding robots in the construction industry, starting from the progress in research and applications. The review identifies the current state of welding robot technology, the technical bottlenecks encountered, and the potential solutions to these challenges, offering valuable insights for the research and development of construction robots. [ABSTRACT FROM AUTHOR]

In order to reduce the energy consumption of the welding robot and ensure the cooperative movement of the robot joints, a trajectory planning method with optimal energy consumption based on improved sparrow search algorithm is proposed. Firstly, the trajectory planning model with optimal energy consumption is established based on the joint torque and angular velocity of the robot. To make the velocity, acceleration and jerk of each joint of the robot be bounded and continuous, the joint space trajectory is constructed with seventh degree B-spline curve. The total energy consumption of the robot is calculated by combining kinematic and dynamic parameters. On the basis of improved sparrow search algorithm, the time series corresponding to the optimal energy consumption is solved by using elite reverse learning, non-dominated sorting and Gaussian-Cauchy variation strategy, and then the optimal continuous motion trajectory of energy consumption is planned. The simulation results show that the proposed method can not only achieve continuous smooth control objective, but also effectively reduce energy consumption. [ABSTRACT FROM AUTHOR]

The main goal of this paper was to connect two controllers of the older generation into one robotic cell, then software implement their synchronized work on servicing and welding certain objects. For this purpose, two controllers manufactured by Yaskawa Motoman were used with the associated manipulators. The hardware solution involved connecting the controllers via General I/O circuit board, where the output of one controller is connected to the input of another and vice versa. The software solution involved parallel programming of two robots for synchronized operation on a common task. During programming, it was necessary to create macro jobs that implemented repetitive actions, such as calling and waiting for robots, grabbing and releasing objects, as well as the actions of starting and stopping the program. The conclusion of presented research is that the robotic cell, formed by two robots that are not intended for synchronization, meets the requirements that until now could only be solved with robots of the newer generation. Proposed solution was confirmed by experimental verification. [ABSTRACT FROM AUTHOR]

The light-weighting of a robotic arm is an important aspect of robot research. In the operation of existing welding robots, excessive vibrations in the welding actuators have been observed, which lead to reduced welding precision and work efficiency. The direct connection between the forearm and the welding actuator is a key component that affects vibrations. Based on this, a study on light-weighting the forearm is proposed. Using the theory of topology optimization with variable density structure, the structural dimensions, shapes, and geometric parameters of the forearm are optimized. The material removal methods of "hole cutting" and "local hollowing" are employed to reconstruct the forearm structure model. Static, modal, and transient simulations were performed on the forearm model pre-optimization and post-optimization. The optimization results show that the mass of the forearm is reduced by 19.8%. The static simulation comparative analysis shows that, under the same constraints and load conditions, the maximum total deformation of the optimized forearm is reduced by 3.6%, the maximum stress is reduced by 3.2%, and the maximum equivalent elastic strain is reduced by 5.7%. The optimized forearm structure is more reasonable and exhibits better mechanical performance. Modal simulation comparative analysis shows that the first and second natural frequencies of the optimized forearm are increased by 9.8% and 7.0%, respectively. Transient simulation comparative analysis demonstrates that, under the maximum operating condition, the vibration frequency and amplitude of the optimized welding robot forearm are reduced by 19.4% and 26.9%, respectively. The maximum amplitudes of the maximum equivalent stress curve and maximum equivalent elastic strain curve are reduced by 51.0% and 46.0%, respectively. This study provides a guarantee for reducing vibrations in welding actuators, improving welding precision, and enhancing the work efficiency of the welding robot. [ABSTRACT FROM AUTHOR]

Aiming to solve the problem that the significant error between the actual joint torque and the calculated joint torque of a welding robot leads to the vibration of the end-effector, which in turn affects the stability of the end-effector, this paper proposes a identification algorithm based on the Weighted Least Squares Genetic Algorithm (WLS-GA) to construct and solve the dynamical model to obtain the accurate dynamical parameters. Firstly, a linear model of welding robot dynamics is derived. The fifth-order optimal Fourier series excitation trajectory is designed to collect experimental data such as joint torque. Then, a rough solution of the parameters to be recognized is obtained by solving the dynamics model through the Weighted Least Squares (WLS) method, the search space is determined based on the rough solution, and the optimal solution is obtained by using the Genetic Algorithm (GA) to perform a quadratic search in the search space. Finally, the identification data obtained from the algorithm is analyzed and compared with the experimental data. The results show that the error between the identification data obtained using the WLS-GA identification algorithm and the experimental data is relatively small. The results show that the identification data obtained using the WLS-GA identification algorithm have less error than the experimental data, taking the Root Mean Square (RMS) value of the joint torque error obtained using the weighted least squares algorithm as a criterion. The accuracy of the WLS-GA identification algorithm can be improved by up to 66.85% compared with that of the weighted least squares algorithm and by up to 78.0% compared with that of the Ordinary Least Squares (OLS) algorithm. In summary, the WLS-GA identification algorithm can accurately identify the dynamic parameters of the welding robot and more accurately construct a dynamic model to solve the effect of joint torque error on the control characteristics of the welding robot. It can improve the stability of the end-effector of the welding robot to ensure the quality of the automobile body and beam welding and welding speed. [ABSTRACT FROM AUTHOR]

In the era of intelligence and automation, robots play a significant role in the field of automated welding, enhancing efficiency and precision. However, challenges persist in scenarios demanding complexity and higher precision, such as low welding planning efficiency and inaccurate weld seam defect detection. Therefore, based on digital twin technology and kernel correlation filtering algorithm, a welding tracking model is proposed. Firstly, the kernel correlation filtering algorithm is used to train the filter on the first frame of the collected image, determine the position of image features in the region, extract histogram features of image blocks, and then train the filter using ridge regression to achieve welding trajectory tracking. Additionally, an intelligent weld seam detection model is introduced, employing a backbone feature network for feature extraction, feature fusion through a feature pyramid, and quality detection of weld seams through head classification. During testing of the tracking model, the maximum tracking error is -0.232 mm, with an average absolute tracking error of 0.08 mm, outperforming other models. Comparatively, in tracking accuracy, the proposed model exhibits the fastest convergence with a precision rate of 0.845, surpassing other models. In weld seam detection, the proposed model excels with a detection accuracy of 97.35% and minimal performance loss at 0.023. In weld seam quality and melt depth error detection, the proposed model achieves errors within the range of -0.06 mm, outperforming the other two models. These results highlight the outstanding detection capabilities of the proposed model. The research findings will serve as technical references for the development of automated welding robots and welding quality inspection. [ABSTRACT FROM AUTHOR]

A torque feedforward vibration suppression tactic, premised on the chaotic-regression tree dynamic model, is proposed to enhance the precision of motion in welding robots during low-velocity movement and to curtail robot oscillation. Chaotic theory is employed to scrutinize the nonlinear characteristics inherent in joint torque amid the low-velocity operation of welding robots. A holistic approach is adopted toward the non-rigid body dynamics component of the joint torque across all joints. By merging ordered fitting with unordered regression tree techniques, the robot kinematic model is derived. The parameters for phase space reconstruction are identified through autocorrelation and pseudo-nearest neighbor methods, improving nonlinear dynamic prediction accuracy via the phase space reconstruction process. To boost the tracking precision of specific motion segments within the trajectory planning, a torque feedforward compensation control algorithm paired with trajectory planning is proposed. Experiments were conducted in low-velocity welding on a 6R welding robot platform, revealing that the improved torque compensation strategy proposed reduces the average position error by 25.2% in comparison with traditional torque compensation tactics. This enhancement optimizes the robot's motion accuracy and concurrently suppresses end effector vibrations. [ABSTRACT FROM AUTHOR]

In this work, a method that integrates deep learning and genetic algorithms is proposed to enhance the precision and efficiency of welding robots and achieve optimal robot path planning. The process involves using SolidWorks to create a 3D model, applying the D-H method to obtain data on the connecting rod parameters, performing theoretical calculations for both forward and inverse kinematics solutions, and utilizing the MATLAB robotics toolbox to validate these solutions. Furthermore, joint space trajectory planning is performed using the quintic polynomial curve method. Through analysis, we identified that abrupt acceleration changes at the initial and final positions significantly impact the smoothness of the motion process. The findings reveal that traditional artificial bee colonies tend to stabilize after 190 iterations, whereas genetic algorithms stabilize around 160 iterations, demonstrating superior convergence speed compared to the traditional ABC algorithm. The optimized approach yields an optimal welding obstacle avoidance path with rapid optimization speed and a stable process. The proposed method effectively addresses the obstacle avoidance path planning challenge for welding robots, showcasing improved convergence speed and stability compared to traditional methods.

This paper describes the method of shaping the product using 3D technology by means of applying arc heating and consumable material – a wire with a diameter of 1.2 mm. The aim of the work is to study the structure and mechanical properties of the product manufactured using additive 3D technology. Each deposited layer consists of three separate beads: two lateral ones, which provide the set contours of the layer, and one middle one, which fills the space between the two lateral ones. Electric arc surfacing was carried out with the help of a welding robot. The use of a robot made it possible to control the time between layer depositions, thereby controlling grain growth. Also, the use of a robot makes it possible to reproduce a set part as accurately as possible according to a pre-calculated and designed model with a minimum error of repetition of the torch movement of ±0.03 mm. As a result, the structure and mechanical properties of the deposited product were investigated. It is shown that the product manufactured according to the presented technology has a fine-grained ferrite-pearlite structure; the grain size ranges from 7 to 10 numbers. The mechanical properties along and across the deposited layers were studied. The indices practically do not differ. A comparison of their values with normative ones showed that they exceeded normative values by 10–50%. 14 Ref., 3 Tabl., 4 Fig. [ABSTRACT FROM AUTHOR]

With the rapid development of vision sensing, artificial intelligence, and robotics technology, one of the challenges we face is installing more advanced vision sensors on welding robots to achieve intelligent welding manufacturing and obtain high-quality welding components. Depth perception is one of the bottlenecks in the development of welding sensors. This review provides an assessment of active and passive sensing methods for depth perception and classifies and elaborates on the depth perception mechanisms based on monocular vision, binocular vision, and multi-view vision. It explores the principles and means of using deep learning for depth perception in robotic welding processes. Further, the application of welding robot visual perception in different industrial scenarios is summarized. Finally, the problems and countermeasures of welding robot visual perception technology are analyzed, and developments for the future are proposed. This review has analyzed a total of 2662 articles and cited 152 as references. The potential future research topics are suggested to include deep learning for object detection and recognition, transfer deep learning for welding robot adaptation, developing multi-modal sensor fusion, integrating models and hardware, and performing a comprehensive requirement analysis and system evaluation in collaboration with welding experts to design a multi-modal sensor fusion architecture. [ABSTRACT FROM AUTHOR]

ObjectivesIn order to solve the problems of the complexity of the existing robot arm pose prediction algorithm model and its over-reliance on the parameters of the camera and robot, a new robot arm pose prediction method based on RGB image gradient vector mapping is proposed. MethodsFirst, a series of robot arm image texture gradient features is calculated based on the Histogram of Oriented Gradient (HOG) algorithm. The mapping relationship between the image features and joint angles of the robot arm is then established by training Deep Neural Networks (DNNs). Finally, the pre-trained vector mapping model is used to quickly predict the pose of the robot arm in a motion frame image. The training and test datasets of the model are generated by synthetic data techniques. ResultsThe results show that the average error of the angle prediction of the three joints of the target robot arm is 2.92°, and the pose prediction time of a single image is about 0.08 s. ConclusionsThe results show that the proposed pose prediction method has better prediction speed and accuracy, and only uses RGB image information to achieve end-to-end pose prediction.

The rapid development of the construction industry has highlighted the urgent need for enhanced construction efficiency and safety, propelling the development of construction robots to ensure sustainable and intelligent industry advancement. Welding robots, in particular, hold significant promise for application in steel structure construction. However, harsh construction environments, variable construction structures, and complex construction conditions present critical technical challenges for weld position, path, and quality for welding robots. This paper aims to provide a focused review of the key technical difficulties faced by welding robots in the construction industry, starting from the progress in research and applications. The review identifies the current state of welding robot technology, the technical bottlenecks encountered, and the potential solutions to these challenges, offering valuable insights for the research and development of construction robots.

The light-weighting of a robotic arm is an important aspect of robot research. In the operation of existing welding robots, excessive vibrations in the welding actuators have been observed, which lead to reduced welding precision and work efficiency. The direct connection between the forearm and the welding actuator is a key component that affects vibrations. Based on this, a study on light-weighting the forearm is proposed. Using the theory of topology optimization with variable density structure, the structural dimensions, shapes, and geometric parameters of the forearm are optimized. The material removal methods of “hole cutting” and “local hollowing” are employed to reconstruct the forearm structure model. Static, modal, and transient simulations were performed on the forearm model pre-optimization and post-optimization. The optimization results show that the mass of the forearm is reduced by 19.8%. The static simulation comparative analysis shows that, under the same constraints and load conditions, the maximum total deformation of the optimized forearm is reduced by 3.6%, the maximum stress is reduced by 3.2%, and the maximum equivalent elastic strain is reduced by 5.7%. The optimized forearm structure is more reasonable and exhibits better mechanical performance. Modal simulation comparative analysis shows that the first and second natural frequencies of the optimized forearm are increased by 9.8% and 7.0%, respectively. Transient simulation comparative analysis demonstrates that, under the maximum operating condition, the vibration frequency and amplitude of the optimized welding robot forearm are reduced by 19.4% and 26.9%, respectively. The maximum amplitudes of the maximum equivalent stress curve and maximum equivalent elastic strain curve are reduced by 51.0% and 46.0%, respectively. This study provides a guarantee for reducing vibrations in welding actuators, improving welding precision, and enhancing the work efficiency of the welding robot.

Copyright of Automobile Technology & Material is the property of Automobile Technology & Material Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The paper presents the concept of an innovative technological line intended for the processing of long linear profiles used in engineering steel and aluminium structures, which can be both hollow and open section profiles. The line is set up with seven main sections: profile loading system, input roller conveyor, plasma arc cutting section, circular saw cutting section, robot welding section, output roller conveyor and profile packaging system. The assumptions adopted to create the concept of the technological line were specified. A block diagram of the line and drawings showing the structure of its selected elements were depicted. The features of the technological line documenting its product and process innovativeness were indicated. The proposed technological line is built in the AGICO Group company, but it can also be successfully implemented in other companies dealing with the processing of long linear profiles.

Aiming to solve the problem that the significant error between the actual joint torque and the calculated joint torque of a welding robot leads to the vibration of the end-effector, which in turn affects the stability of the end-effector, this paper proposes a identification algorithm based on the Weighted Least Squares Genetic Algorithm (WLS-GA) to construct and solve the dynamical model to obtain the accurate dynamical parameters. Firstly, a linear model of welding robot dynamics is derived. The fifth-order optimal Fourier series excitation trajectory is designed to collect experimental data such as joint torque. Then, a rough solution of the parameters to be recognized is obtained by solving the dynamics model through the Weighted Least Squares (WLS) method, the search space is determined based on the rough solution, and the optimal solution is obtained by using the Genetic Algorithm (GA) to perform a quadratic search in the search space. Finally, the identification data obtained from the algorithm is analyzed and compared with the experimental data. The results show that the error between the identification data obtained using the WLS-GA identification algorithm and the experimental data is relatively small. The results show that the identification data obtained using the WLS-GA identification algorithm have less error than the experimental data, taking the Root Mean Square (RMS) value of the joint torque error obtained using the weighted least squares algorithm as a criterion. The accuracy of the WLS-GA identification algorithm can be improved by up to 66.85% compared with that of the weighted least squares algorithm and by up to 78.0% compared with that of the Ordinary Least Squares (OLS) algorithm. In summary, the WLS-GA identification algorithm can accurately identify the dynamic parameters of the welding robot and more accurately construct a dynamic model to solve the effect of joint torque error on the control characteristics of the welding robot. It can improve the stability of the end-effector of the welding robot to ensure the quality of the automobile body and beam welding and welding speed.

In order to understand the physical heat dissipation structure of welding robot controllers, the author proposes a research based on the design and simulation analysis of the physical heat dissipation structure of welding robot controllers. The author first analyzed that the design of welding heating system is the key to the research of welding robot heating technology, which is divided into the design of induction heating system temperature control circuit and temperature control program. The induction heating system is closely related to power electronics technology, with inverter design and soft switching technology being the focus and difficulty of this chapter. Secondly, using modular design methods, an induction heating system with a frequency of 450KHz and a power of 100 W is designed. This part is connected through an optocoupler and an induction heating system for power regulation and temperature control. Starting from designing the minimum system of a microcontroller, through keyboard input, temperature signal processing, analog-to-digital conversion, and finally to digital tube display output, the design of each module of the temperature control circuit was completed. Finally, in order to verify the effectiveness of the design, actual heat dissipation testing is required. By establishing an appropriate testing environment in the laboratory, the temperature changes and heat dissipation efficiency of the controller under different working conditions can be measured. Based on the actual test results, further adjustments and improvements can be made to the design to meet the heat dissipation needs of the welding robot.

Copyright of China Mechanical Engineering is the property of Editorial Board of China Mechanical Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In view of the nonlinear problem of backlash caused by the gear transmission structure in the automatic pipe pile welding machine, an improved sliding mode controller design method based on the extended state observer is proposed. Firstly, the nonlinear and time-varying backlash model is equivalent to a global linearization model, and it is proved that the upper limit of the modeling error is bounded. For the situation with nonlinear input backlash and unknown external disturbance, a sliding mode controller and an improved sliding mode controller based on extended state observer are designed, respectively. The former can track the input signal asymptotically and stably, and has strong anti-interference ability, but it has large chattering. The latter uses the extended state observer to detect the unknown disturbance and directly compensates to the controller, which not only ensures the tracking error within the expected accuracy range, but also reduces chattering. The simulation results show that compared with the traditional sliding mode controller, the improved sliding mode controller system based on the extended state observer reaches the sliding mode surface faster and chatters less. [ABSTRACT FROM AUTHOR]

Introduction. One of the tasks of two-link manipulators of industrial robots that move the end-effector along complex trajectories (e.g., robot welder) is associated with the need for careful programming of their movement. For these purposes, manual programming methods or training methods are used. These methods are quite labor-intensive, and they require highly qualified service personnel. A possible solution to the problem of programming the manipulator movements is the simulation of motion with the calculation of angular coordinates. This can help simplify the geometric adaptation of the manipulator in the process of debugging the control program. Therefore, this work aimed at calculating coordinates for programming the control system of a two-link manipulator operating in an angular coordinate system and moving the end-effector along a complex trajectory (e. g., when welding car bodies). Materials and Methods. A two-link robot manipulator designed for cyclically repeating actions in an angular coordinate system was considered. The manipulator consisted of two rotating links: “arm” and “elbow”, which were fixed on the base. The base could rotate, which provided a third degree of freedom. This configuration increased the working area of the manipulator and minimized the area for its placement in production. The movement of the manipulator end-effector could be performed if the kinematics provided its positioning along three Cartesian and three angular coordinates. For software control of robots, including welding robots operating in an angular coordinate system and performing the movement of the end-effector along a complex trajectory, it was required to calculate the angular coordinates of the movement of the end-effector of a two-link articulated manipulator. The robot control system should determine the position of the tool in the angular coordinate system, converting it for user friendliness into x, y and z coordinates of the Cartesian coordinate system. Results. The relations of angular and Cartesian coordinates have been obtained. They can be used for calculating when programming the control system of a two-link manipulator of an industrial robot and organizing the exchange of information between the user and the control system, as well as for checking the accuracy and debugging the movement of the end-effector of an industrial robot through feedback. Discussion and Conclusion. The presented results can be used for software control of a welding robot operating in an angular coordinate system and performing a complex trajectory of the end-effector of a two-link articulated manipulator (gripper). A manipulator operating in an angular coordinate system can be used for contact spot welding when moving the end-effector along a complex trajectory using a positioning or contouring control system. These systems control the movement of the end-effector along a given trajectory with the help of technological commands.

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. [ABSTRACT FROM AUTHOR]

In order to improve the welding efficiency of the ship welding robot, the path planning of the welding robot based on immune optimization is proposed by taking the welding path length and energy loss as the optimization goals. First, on the basis of the definition of the path planning of the welding robot, the grid modeling of the robot's working environment and the triangular modeling of the welding weldments are carried out. Then, according to the working process of the welding robot, the length objective function, including the welded seam path and the welding torch path without welding, is constructed, and the energy loss function is constructed based on the kinematics and Lagrange function. Finally, the immune optimization algorithm based on cluster analysis and self-circulation is introduced to realize the multi-objective optimization of the path planning for the ship welding robot. The test results of four kinds of ship welding weldments show that compared with the simple genetic algorithm, immune genetic algorithm, ant colony algorithm, artificial bee colony, particle swarm optimization, and immune cloning optimization, the proposed multi-objective immune planning algorithm is the best in terms of planning path length, energy consumption, and stability. Furthermore, the average shortest path and its standard deviation, the average minimum energy consumption and its standard deviation, and the average lowest convergence generation and its standard deviation are reduced by an average of 9.03%, 54.04%, 8.23%, 19.10%, 27.84%, and 52.25%, respectively, which fully verifies the effectiveness and superiority of the proposed welding robot path planning algorithm. [ABSTRACT FROM AUTHOR]

It is extremely important to monitor the health status of welding robots for the safe and stable operation of a body-in-white (BIW) welding production line. In the actual production process, the robot degradation rate is slow and the effective data are poor, which can reflect a degradation state in the large amount of obtained monitoring data, which causes difficulties in health status evaluation. In order to realize the accurate evaluation of the health status of welding robots, this paper proposes a health status evaluation method based on the evidential reasoning (ER) rule, which reflects the health status of welding robots by using the running state data monitored in actual engineering and through the qualitative knowledge of experts, which makes up for the lack of effective data. In the ER rule evaluation model, the covariance matrix adaptive evolutionary strategy (CMA-ES) algorithm is used to optimize the initial parameters of the evaluation model, which improved the accuracy of health status evaluations. Finally, a BIW welding robot was taken as an example for verification. The results show that the proposed model is able to accurately estimate the health status of the welding robot by using the monitored degradation data. [ABSTRACT FROM AUTHOR]

Fault diagnosis for body-in-white (BIW) welding robots is important for ensuring the efficient production of the welding assembly line. As a result of the complex mechanism of the body-in-white welding robot, its strong correlation of components, and the many types of faults, it is difficult to establish a complete fault diagnosis model. Therefore, a fault diagnosis model for a BIW-welding robot based on a multi-layer belief rule base (BRB) was proposed. This model can effectively integrate monitoring data and expert knowledge to achieve an accurate fault diagnosis and facilitate traceability. First, according to the established fault tree, a fault mechanism was determined. Second, based on the multi-layer relationship of a fault tree, we established a multi-layer BRB model. Meanwhile, in order to improve the accuracy of the model parameters, the projection covariance matrix adaptive evolutionary strategy (P-CMA-ES) algorithm was used to optimize and update the parameters of the fault diagnosis model. Finally, the validity of the proposed model was verified by a simulation experiment for the BIW-welding robot. [ABSTRACT FROM AUTHOR]

In China, steel structure building has become an important direction of national support and development. As a link in steel structure construction, welding plays a vital role. With the continuous development of domestic steel structures in the direction of "big, special, and new", manual welding becomes increasingly difficult. The application of robotic technology can effectively reduce the problems of unstable quality and low efficiency caused by manual welding. However, how to evaluate the overall application effect of this technology from the perspective of steel structure construction projects is an urgent problem to be solved at present. Through an in-depth analysis of the technology of building steel structure welding robots, combined with the idea of the capability maturity model and WSR methodology, the evaluation index system of application maturity of building steel structure welding robotic technology is designed. In addition, according to the gray, fuzzy, and difficult-to-quantify characteristics of the evaluation index system, the evaluation model of the application maturity of the building steel structure welding robot technology is established by using the subjective and objective combination weighting method and the gray system theory. In this model, the mixed weighting method of AHP and entropy weight method is used to determine the index weight, and then the multi-level gray theory is used to comprehensively evaluate the maturity of the technology application. Lastly, a project is used as an example to check the science and feasibility of the model. [ABSTRACT FROM AUTHOR]

Multi-objective welding robot path planning is becoming an important problem owing to the developing requirements of industrial production intelligence. An approach with path planning and optimization is proposed for solving the problem of arc welding. A rapidly exploring random tree* (RRT*)-based local path search algorithm is applied to generate a set of collision-free paths between any two welding seams, and the global search algorithm based on the decomposition-based multi-objective evolutionary algorithm (MOEA/D) framework is introduced to improve welding production efficiency by optimizing the requested contradictory objectives, namely, path length, trajectory smoothness and energy consumption. Both proposed algorithms are tested in different instances and on an actual welding workpiece, and the results prove that the proposed method could be useful in industrial production. [ABSTRACT FROM AUTHOR]

A method for welding line detection using point cloud data is proposed to automate welding operations combined with a contact sensor. The proposed system targets a fillet weld, in which the joint line between two metal plates attached vertically is welded. In the proposed method, after detecting the position and orientation of two flat plates regarding a single viewpoint as a rough measurement, the flat plates are measured from the optimal shooting position in each plane in detail to detect a precise weld line. When measuring a flat plate from an angle, the 3D point cloud obtained by a depth camera contains measurement errors. For example, a point cloud measuring a plane has a wavy shape or void owing to light reflection. However, by shooting the plane vertically, the point cloud has fewer errors. Using these characteristics, a two-step measurement algorithm for determining weld lines was proposed. The weld line detection results show an improvement of 5 mm compared with the rough and precise measurements. Furthermore, the average measurement error was less than 2.5 mm, and it is possible to narrow the range of the search object contact sensor for welding automation. [ABSTRACT FROM AUTHOR]

For spot-welding process, rational path planning of weld points can improve productivity for welding robot. In basic ant colony optimization, at the beginning of the iteration, the pheromone concentration is only related to the path length, but at this time, the path often contains a lot of redundant parts. Therefore, the pheromone in the initial iteration is almost difficult to reflect the advantages and disadvantages of the node, and it requires multiple iterations to slowly show the advantages and disadvantages of the path. For this shortcoming, a Monte Carlo-based improve ant colony optimization (MC-IACO) is proposed to solve the path planning of welding robots. The MC-IACO algorithm samples the path results generated in each generation and converts them into Monte Carlo indexes of the nodes. By substituting the Monte Carlo index of the feasible node into the sigmoid function, the probability that the corresponding node may constitute the optimal path, namely the Monte Carlo factor, is calculated to help ants make decisions. The new node transfer formula constructed with this factor can effectively improve the path finding efficiency of ants and the efficiency of the algorithm to complete the path planning task. The feedback adjustment factor is introduced to make the judgment of the advantages and disadvantages of feasible nodes also refer to the advantages and disadvantages of subsequent nodes. The simulation results show that compared with the basic ant colony optimization and other improved ant colony optimization, the MC-IACO algorithm in this paper improves significantly in solving the path planning problem of the welding robot, and its overall performance is better.

With the rapid development of vision sensing, artificial intelligence, and robotics technology, one of the challenges we face is installing more advanced vision sensors on welding robots to achieve intelligent welding manufacturing and obtain high-quality welding components. Depth perception is one of the bottlenecks in the development of welding sensors. This review provides an assessment of active and passive sensing methods for depth perception and classifies and elaborates on the depth perception mechanisms based on monocular vision, binocular vision, and multi-view vision. It explores the principles and means of using deep learning for depth perception in robotic welding processes. Further, the application of welding robot visual perception in different industrial scenarios is summarized. Finally, the problems and countermeasures of welding robot visual perception technology are analyzed, and developments for the future are proposed. This review has analyzed a total of 2662 articles and cited 152 as references. The potential future research topics are suggested to include deep learning for object detection and recognition, transfer deep learning for welding robot adaptation, developing multi-modal sensor fusion, integrating models and hardware, and performing a comprehensive requirement analysis and system evaluation in collaboration with welding experts to design a multi-modal sensor fusion architecture.

To improve the automation, welding efficiency, and welding quality of duckbill welding of the cotton seeder, this study designed a cotton seeder duckbill welding robot. According to the characteristics of the duckbill weldment and welding requirements, the overall structure of the welding robot was determined, including the girdle feeding mechanism, static duckbill feeding mechanism, hinge feeding mechanism, welding fixture, welding actuator, and control system. To realize the continuous automatic feeding, positioning, fixing, welding, and unloading of the workpiece in the duckbill welding, the feeding mechanism adopts the method of cooperative cooperation of inductive proximity switch, electromagnet, and cylinder. The main body of the welding fixture adopts the pneumatic clamping method; the welding actuator adopts the synchronous belt module electric drive so that the welding torch can move in a straight line along the X axis and the Z axis. The welding process of the duckbill was simulated by Simufact Welding software, and the deformation and stress changes of the weldment were compared and analyzed when the single-sided single welding, the bilateral symmetrical double welding torch, two welding forms, and two welding process parameters were used to determine the welding process parameters of the welding robot. The prototype was made and the welding test was carried out. The test results show that the duckbill welding robot of the cotton seeder has stable feeding, solid clamping, accurate positioning, and high welding efficiency. According to the national standard, the appearance of the duckbill weld is inspected. The surface of the duckbill weld and the heat-affected zone has no cracks, incomplete fusion, slag inclusion, crater, and porosity. The forming quality of the welded parts is good. The design of the duckbill welding robot for cotton seeder is helpful in solving the problems of cumbersome positioning and clamping and low efficiency in manual and semi-automatic duckbill welding robots, which provides a strong guarantee for the large-scale and standardized welding production of the dibbler duckbill. [ABSTRACT FROM AUTHOR]