Tasks for a sensor-controlled robot

Intelligent manufacturing is the theme and main direction of the “Made in China 2025” development strategy, and the application of industrial robots is an important direction of intelligent manufacturing. In the next few years, industrial robots will be widely used in various enterprises, which will inevitably require a large number of high-tech industries. Industrial robots are high-tech products of modern society and play an important role in the process of economic development, especially in the manufacturing industry. Industrial robot technology is widely used in automated production lines, so that industrial production efficiency can be greatly improved. Instead of manual labor to carry out various complex production and operations, to achieve industrial production automation. Analyze the application of industrial robots in automated production lines at this stage, and explore their future development directions, so that they can better serve the manufacturing industry. This article takes the industrial robots and PLCs in the industrial automation production line as the research object, and takes the automated production line for mass production of a product as an example. It explains the joint control scheme of the PLC controller and the industrial robot controller, and provides for the construction of joint control of similar production lines in the future.

Industrial robots play a vital role in transforming and upgrading the manufacturing industry. They harness automation technologies to drive industrial production and enhance their value through innovations in production tools and knowledge. This paper analyzes annual data from China's A‐share nonfinancial manufacturing listed companies during the period from 2007 to 2019, examining the impact of industrial robot applications on corporate cash holdings. The study discovers that the application of industrial robots notably reduces corporate cash holdings, thereby confirming the effect of capital allocation. The analysis rules out the possibility that this reduction occurs through alleviating agency problems. Mechanism analysis reveals that the application of industrial robots reduces cash holdings for precautionary motives by reducing labor leverage and enhancing labor productivity and operational efficiency. Additional tests reveal that the reduction in corporate cash holdings due to industrial robot applications is more pronounced in enterprises with intense market competition, labor‐intensive and nonstate‐owned enterprises. This study deepens the research focus on industrial robot applications and corporate cash holdings, providing a theoretical basis for policymakers to promote technological innovation and industrial advancement.

The production process of any type of product today is difficult to imagine without the use of industrial robots. Their versatility, production flexibility and wide technological capabilities make them an indispensable tool in modern manufacturing, including in such economically and strategically important industry as shipbuilding. In this regard, according to the authors, it is advisable to analyze the current situation and prospects for the use of robotization in industry, in particular, shipbuilding in Russia and abroad. The article presents statistical data on indicators of the level of robotization of domestic and foreign industry; describes the trends in the development of industry during its robotization, indicates the scope of application of industrial robots, etc. The factors of expediency of using robots in industry are analyzed. The inevitability of the general growth of industrial robotization and, as a result, a change in the economic structure in developed countries and, possibly with a certain lag in Russia has been substantiated. Identified problematic issues associated with the introduction and use of industrial robots in the domestic industry, in particular, shipbuilding.

Industrial robot application technology is an important course for mechanical college students, and robot is a kind of relatively expensive equipment. So in the daily learning process of robots, there may not be so many objects for everyone to learn and train. In this paper, virtual reality technology is used to simulate the industrial robot and its scene. In this paper, three-dimensional modeling is completed by Solidworks software, and the industrial robot body is constructed. Then this paper uses 3DS Max software to model the application environment, assembly line and classroom which need industrial robot. Finally, this paper uses Unity3D software for virtual reality programming and simulation design. Through the design, this paper based on virtual reality technology for industrial robot technology and application courses teaching, building the basic line. This has laid a solid foundation for the later stage virtual reality technology to perfect the aspect of teaching.

In this study, we aim to explain the large disparities among countries and regions on industrial robot application in terms of robot density and robot growth. Based on the premise that people in all cultures have the same potential for innovation, we propose a cross-level lens of cultural tightness-looseness to predict that, in the nascent robotics industry where rules and regulations are underdeveloped (i.e., a loose domain), people in tight cultures (e.g., Singapore, Japan, China) are more likely to innovate than those in loose cultures (e.g., the UK, U.S., the Netherlands) because their creativity is permitted in this or a few other loose domains only. We test this theoretical lens using multi-source longitudinal archival data on robot applications. Several significant findings emerge. First, there is a significant positive relationship between cultural tightness and robot application across 32 countries and territories from 1993 to 2022 (Study 1). Second, such a positive relationship also appears across 50 states in the United States from 1998 to 2022 (Study 2a), and across 31 provinces in China from 2008 to 2022 (Study 2b). Finally, the interaction effect between country- and region-level cultural tightness on robot application is significant (Study 3). These findings provide strong empirical support for our cross-level lens of cultural tightness and shed light on how cultural tightness at different levels interacts to affect incremental innovation (i.e., robot application) in a loose domain (i.e., the robotics industry). Moreover, these findings suggest that loosening tight control on certain domains of a tight culture would remarkably boost creativity and incremental innovation in these domains.

Although many algorithms perform very well on certain datasets, existing stereo matching algorithms still fail to obtain ideal disparity images with high precision in practical robotic applications with weak or untextured objects. This greatly limits the application of binocular vision for robotic arm guidance. Traditional stereo matching algorithms suffer from disparity loss, dilation and other problems, and deep learning algorithms have weakly generalization ability, making high‐accuracy results impossible with non‐training images. We propose an algorithm that uses segments and edges as matching units. We find the mapping relationship between two‐dimensional images and three‐dimensional scenes using segments. The algorithm obtains highly accurate results in industrial robotic applications with mainly planar facets. We combine it with a deep learning algorithm to obtain very good high‐accuracy results in both general scenes and applications of industrial robots. The algorithm effectively improves the non‐linear optimization ability of traditional algorithms and generalization ability of deep learning, and provides an effective method for the binocular vision guidance of industrial robotic scenes. We used the algorithm to guide the robot arm for threading with a success rate of 70%.

With the rapid development of industrial automation, the traditional manual operation is no longer suitable for the development of modern enterprises, because the industrial robot control system dynamic response is fast, high position accuracy, strong overload capacity, so it is very suitable for t he production of mechanical parts and processing line automation transformation. In this paper, an air conditioning compressor company to the pump body production line for the theme of automation, the application of industrial robots instead of artificial automation production. Aiming at the transformation of the L2 series pump body assembly line in the assembly plant of the company, the industrial robot was used to transform the production line, and the program debugging was carried out on the site. The robot was able to run stably and work as required. At last, the actual working beat of the robot is calculated to be 13.7 seconds, which is 2.3 seconds less than 16 seconds in manual operation. Experimental results show that the actual working tempo of the robot can meet the requirements, and can improve the assembly efficiency and save manpower.

Most industrial robots are still controlled with motor-side feedback. To increase the accuracy of industrial robots, controllers with joint-side feedback and explicit consideration of the joint elasticity, such as linearization-based controllers, are needed. The key issue for the performance of linearization-based controllers is a high-fidelity model. Today, the drivetrains installed in the joints of industrial robots of the high payload class usually consist of a permanent magnet synchronous machine and a cycloidal drive. Such robot joints are highly nonlinear due to effects like hysteresis, torque ripples and friction. Therefore, the drivetrain dynamics are crucial for the experimental performance of linearization-based controllers for industrial robots. This paper identifies the challenges in linearization-based control of industrial robots with such a drivetrain configuration based on experimental results on a KUKA KR-210-2. Using an exemplary approach, it is shown that a linearization-based controller does not provide the theoretical performance due to needed model simplifications. For this purpose, simulation and experimental results are compared to a linear robot controller with motor-side feedback. These results indicate why such controllers are still a valid alternative for the practical application of similar industrial robots.

With the wide application of mobile robots in industry, path planning has always been a difficult problem for mobile robots. Reinforcement learning algorithms such as Q-learning play a huge role in path planning. Traditional Q-learning algorithm mainly uses - greedy search policy. But for a fixed search factor -greedy. For example, the problems of slow convergence speed, time-consuming and many continuous action transformations (such as the number of turns during robot movement) are not conducive to the stability requirements of mobile robots in industrial transportation. Especially for the transportation of dangerous chemicals, continuous transformation of turns will increase the risk of objects toppling. This paper proposes a new method based on - greedy 's improved dynamic search strategy is used to improve the stability of mobile robots in motion planning. The experiment shows that the dynamic search strategy converges faster, consumes less time, has less continuous transformation times of action, and has higher motion stability in the test environment.

The days when humans and robots have not yet interacted in daily activities are gone. In fact, robots are on their way to changing their applications from industry to contributing to the well-being of people in everyday life. These robots are called "social robots" (SR). Unlike robots that simply describe what helps them, social robots aim to establish social interactions and improve the socialization of human beings. While many industrial robots are primarily used by manufacturing companies for hazardous or menial tasks, social robots have become a popular choice due to their quality and the positive impact they have on productivity and profitability. Industrial robots have anthropological features and are generally reprogrammable machines. Their mechanical arms are crucial components, and they possess other, albeit less prominent, features such as decision-making abilities, a range of emotions, the ability to respond to inputs, and communication skills. They are widely used in various industries, including material handling, assembly, and machines for applications like material handling, assembly, and machines for applications. These robots play an essential role in increasing efficiency and quality. Robots in manufacturing companies are highly valued for their ability to automate tasks and be reprogrammed for different functions. They possess various features optimized for specific handling tasks, including the ability to move in two or more axes and respond to different sensory inputs. This comprehensive set of features makes them suitable for a wide range of applications, including assembly, welding, material handling, loading, packaging, and inspection, where endurance, speed, and accuracy are required. The selection of industrial robots is a decision-making process based on the needs of production. Making the right decision is crucial for productivity and success. Choosing the wrong robot can lead to issues such as inefficiency or the inability to perform specific tasks within a multi-scheduled production. In the worst-case scenario, a completely unsuitable robot can render the entire company unusable. The complexity of the selection process is amplified by the diversity of robot manufacturers, as well as the significant variations in manufacturing jobs. Manufacturers themselves have recognized the importance of addressing these challenges, particularly in relation to the demands and intensity of specific tasks. Unity of ideal solution (TOPSIS). is prioritized by, this is a multi-criteria decision Analytical method. TOPSIS Abbreviation of (PIS). Select The short geometric distance alternative is positive The best solution is, basically The Great Solution of Thought (Nis) To be negative Distance is geometric. TOPSIS The assumption is even higher is, is coming or going The benchmarks are increasing. Scaling problems or Many in the criteria Parameters Mostly Improper Dimensions Due to normalization Generally required. Alternative taken as load capacity, Maximum tip speed, Memory capacity, Manipulator reach, Repeatability, Positioning accuracy. Evaluation parameter taken as Industrial robot 1, Industrial robot 2, Industrial robot 3, Industrial robot 4, Industrial robot 5, Industrial robot 6, Industrial robot 7. From the result it is seen that Industrial robot 3 is got the first rank where as is the Industrial robot 1 is having the lowest rank. Keywords: Industrial Robot, Manufacturing industry, Tools or Facilitator teachers.

This paper proposes a novel force-sensor-less contact motion control for quick and smooth industrial robot motion. Industrial robots serve important functions in modern industrial society. However, their general application is limited because they employ only position based high-stiffness control methods. The proposed method achieves smooth contact motion for new applications of industrial robots, and it solves two of the problems of contact motion control. First, impulsive force is reduced through active braking motion control. Second, wasted motion is decreased by applying integral-proportional(I-P) force control after contact. Experimental results show the validity of the proposed method with a three-degree-of-freedom(DOF) robot. The proposed method achieves a 78.7% decrease in settling time and a 6% reduction in impulsive force. The proposed method has the potential to improve fast contact motion through a profile control application.

Does industrial robot application promote green technology innovation in the manufacturing industry?

Many tasks in the meat processing industry involve repetitive and physically demanding work. Therefore, the workers are highly susceptible to repetitive-strain injuries to their hands, wrists, elbows, and back. Additionally, quality control and hygiene requirements are vital to this industry. For these reasons, industrial robots have been considered for automating processes such as animal slaughtering, meat cutting and meat selecting. This paper presents an assessment of the requirements for industrial robots in meat processing. Results from a conducted study are disclosed for the existing and potential robotic applications. The meat processes in detail, requirements, challenges and barriers of robotic automation are described, robotic research activities are introduced, existing robotic applications are analyzed and studied and potential applications are proposed and discussed.

ROBOT APPLICATIONS IN GERMANY

This paper investigates the relationship between industrial robot applications and export growth using data from 54 major exporting countries from 2010 to 2018. We find that industrial robot applications have positive effects on exports by reducing export costs and upgrading product technology. This effect is stronger in economically advanced countries. Moreover, technological innovation and educational investment amplify the impact of industrial robots. These findings offer valuable insights for policymakers seeking to optimize industrial robot integration to foster export.