Vision Guided Parallel Robot and Its Application 
For Automated Assembly Task

Bulej, Vladimír; Stanček, Ján; Kuric, Ivan

doi:10.12913/22998624/91887

Cited by 12 publications

(7 citation statements)

References 5 publications

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“…The FANUC i RVision system is a fully robot integrated visual sensor system designed to eliminate such restrictions. 38,39 i RVision system uses one or more cameras to find the precise position and orientation (or other desired parameter, e.g. color, different size/scale factor) of each object within the scene and modifies preprogramed robot trajectory.…”

Section: Workplace Structure and Equipmentmentioning

confidence: 99%

“…of the objects is different from their position set when the robot program was taught. 38 The i RVision application solution can be implemented on any FANUC industrial robot equipped with suitable hardware card for its connection and can be customized (different capability 2D, 2½D or 3D vision, different tasks, etc.). The main advantages and reasons for application of integrated i RVision system are reduced capital and operating costs, reduced complexity of whole system, stable running due to the elimination of third-party hardware and software features, and high speed of vision communication and processing through robot backplane.…”

Section: Workplace Structure and Equipmentmentioning

confidence: 99%

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Case study: Performance analysis and development of robotized screwing application with integrated vision sensing system for automotive industry

Sága

Bulej

Čuboňová

et al. 2020

International Journal of Advanced Robotic Systems

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Industrial cameras starting to play a significant role in current industrial environment and they represent a strong tool for robotics mainly in cases when they are combined with high-speed robots. However, there are still some difficulties in vision system integration. The capability of such system (e.g. assembly or technological system) depends on several factors, for instance, the camera position, lightning conditions, pattern recognition algorithms, precise setup, as well as well-trained programmer and engineer. The skills of the engineering staff and the precise analysis of conditions and process requirements seem to be crucial for successful solution, what was proved also in our experimental test. The main aim of the article is development and complex performance analysis of robotized screwing application with integrated vision system, concretely the case study of automated assembly system in automotive industry—bolting tightening robotized station as a part of car seat assembly process. The main key elements of the designed workplace are industrial robot FANUC M-20 iA/20M with integrated iRVision system containing the industrial camera Sony XC-56. The real influence of inaccuracies during the design process, gradual “step-by-step” refinement, and final influence of all changings on the final quality and efficiency of designed system was demonstrated. At the end, we reached the point where the total number of screwing operations with NOK results (not OK / negative results) is about six single negative results per day, which represents less than 0.1% of all recognitions (overall reliability is higher than 99.9%).

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Section: Workplace Structure and Equipmentmentioning

confidence: 99%

Section: Workplace Structure and Equipmentmentioning

confidence: 99%

Case study: Performance analysis and development of robotized screwing application with integrated vision sensing system for automotive industry

Sága

Bulej

Čuboňová

et al. 2020

International Journal of Advanced Robotic Systems

Self Cite

View full text Add to dashboard Cite

show abstract

“…In both basic ways, the person evaluates the image and then evaluates the result of the inspection using subjective opinion. Due to the disadvantages of such an inspection, which are monotony and the subjective evaluation of the results is an attempt to automate these processes [11,12]. In various fields, the common approaches to evaluating the acquired image is sufficient, e.g., comparing reference images with inspected ones [13], searching for elements using the speeded-up robust features method, and many others.…”

Section: Introductionmentioning

confidence: 99%

Approach to Automated Visual Inspection of Objects Based on Artificial Intelligence

et al. 2022

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The article discusses the possibility of object detector usage in field of automated visual inspection for objects with specific parameters, specifically various types of defects occurring on the surface of a car tire. Due to the insufficient amount of input data, as well as the need to speed up the development process, the Transfer Learning principle was applied in a designed system. In this approach, the already pre-trained convolutional neural network AlexNet was used, subsequently modified in its last three layers, and again trained on a smaller sample of our own data. The detector used in the designed camera inspection system with the above architecture allowed us to achieve the accuracy and versatility needed to detect elements (defects) whose shape, dimensions and location change with each occurrence. The design of a test facility with the application of a 12-megapixel monochrome camera over the rotational table is briefly described, whose task is to ensure optimal conditions during the scanning process. The evaluation of the proposed control system with the quantification of the recognition capabilities in the individual defects is described at the end of the study. The implementation and verification of such an approach together with the proposed methodology of the visual inspection process of car tires to obtain better classification results for six different defect classes can be considered as the main novel feature of the presented research. Subsequent testing of the designed system on a selected batch of sample images (containing all six types of possible defect) proved the functionality of the entire system while the highest values of successful defect detection certainty were achieved from 85.15% to 99.34%.

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“…Saga et al [1] mentioned that advanced digital technology is already used in industry, however with the concept of Industry 4.0 it transforms production into smarter automation in various ways through the installation of industrial and collaborative robots, intelligent sensors, advanced monitoring methods, the application of production simulations, virtual reality and virtual commissioning [2]. Modern advanced machine vision systems based on "smart camera sensors" have opened new applications and rapidly spread into many industrial areas, such as general process control, object identification and recognition, as well as quality control [3,4]. It is the implementation of advanced production monitoring systems at all its levels of production systems and especially in assembly operations that can have a significant positive impact on the final quality of the product.…”

Section: Introductionmentioning

confidence: 99%

Conceptual Design and Simulation of Cable-driven Parallel Robot for Inspection and Monitoring Tasks

2022

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The paper deals with the conceptual design of cable-driven parallel robot which will be used for inspection and monitoring tasks in production process. The reason and need of vision based control of the production process is described in the introduction. Furthermore, mechanisms with parallel kinematic structure are described, as well as their usage in industry and sports broadcasts. On that basis, there is proposed the conceptual design of the cable driven parallel robot (CDPR) for desired task of visual monitoring of production line. Finally, there is proposed a simulation of designed robotic system and workspace shape analysis.

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Vision Guided Parallel Robot and Its Application For Automated Assembly Task

Cited by 12 publications

References 5 publications

Case study: Performance analysis and development of robotized screwing application with integrated vision sensing system for automotive industry

Case study: Performance analysis and development of robotized screwing application with integrated vision sensing system for automotive industry

Approach to Automated Visual Inspection of Objects Based on Artificial Intelligence

Conceptual Design and Simulation of Cable-driven Parallel Robot for Inspection and Monitoring Tasks

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