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EN
During the years common understanding of the possibilities and perspectives of Virtual Reality (VR) usage has been changed. It is thought that VR is mainly used in entertainment purposes, but it is being used already for many years in different industries, and now with easier access to the hardware it became a helpful and accessible tool that could be used and developed in any field of human activities. In manufacturing, immersive technologies are mainly used nowadays for the visualisation of processes and products combining those visuals into the factory Digital Twin (DT) which is possible to view from the inside look. This feature is already being used in several manufacturing simulation tools, which enable to view onto industrial line / robotic cells via Virtual Reality glasses. However, the potential of using simulations with VR in manufacturing is not fully uncovered. The main aim of this, industrial robotics targeted research is to enable besides simulation also universal control algorithms through Virtual Reality experience, produced by game engine Unity3D, which can be easily modified for a wide range of industrial equipment. The primary outcome of this work is the development of the synchronisation model of real and virtual industrial robots and experimental testing the developed model in Virtual Reality and shop floor labs.
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Industrial robots are mainly used stationarily in one working position. SMEs often find themselves in situations where robots don’t have enough work to do, and because in general, robots cannot be easily moved to another position, the efficiency of robots will decrease. This study provides a solution for this issue. The solution can be found in a robot work cell where a mobile robot deals with robot arm transportation. However, since the mobile robot is not precise enough in positioning, machine vision is used to overcome this problem, which helps the robot to position itself accurately in relation to the work object. The solution has been developed and tested successfully at an Industry 4.0 testbed.
EN
Digital Twin (DT) concept nowadays is shown via the simulations of the manufacturing systems and included those production processes and parametric 3D models of the product. It is the primary method for planning, analysing and optimising the factory layout and processes. Moreover, work on management via the simulation in real-time is already done using Virtual Reality (VR) tools from a safe and remote environment. However, there is a list of limitation of such kind of digital systems, as connectivity speed and precision of the digital environment. The primary goal of this study is to access second listed limitation and on the example of the fully synchronised physical with its digital replica industrial robot, increase the level of precision of the developed DT environment. The proposed approach introduces transfer of the mathematical model to the virtual environment, thus creating a precise and scaled visual model of the Industrial Robot.
EN
Autonomous driving is no longer just an idea of technology vision instead a real technical trend all over the world. The continuing development to a further level of autonomy requires more on mobile robots safety while bringing more challenges to human-vehicle interaction. A robot autonomous vehicle (AV) as a research platform operates an experimental study on human-AV-interaction (HAVI) and performs a novel method for mobile robot safety assurance. Not only autonomous driving technology itself but human cognition also performs an essential role in how to ensure better autonomous mobile robot safety. A Wizard-of-Oz experiment in the university combing a survey-based study indicates public attitudes towards driverless robot vehicles. HAVI experiment have been carried through light patterns designed for experiment. This paper presents an attempt to investigate humans’ acceptance and emotions as well as a validation to bring the mobile robot vehicle to a high-level autonomy.
EN
Modern manufacturing faces vastly changing challenges. The current economic situation and technological developments in terms of Industry 4.0 (I4.0) and Industry 5.0 (I5.0) force enterprises to integrate new technologies for more efficient and higher-quality products. Artificial intelligence (AI) and Machine Learning (ML) are the technologies that make machines capable of making human-like decisions. In the long run, AI and ML can add a layer (functionality) to make IoT devices more interactive and user-friendly. These technologies are driven by data and ML uses different types of data for making decisions. Our research focuses on testing a cobot-based quality control (CBQC) system that uses smart fixture and machine vision (MV) to determine the cables inside products with similar designs, but different functionality. The products are IoT modules for small electric vehicles used for interface, connectivity, and GPS monitoring. Previous research describes the methodology of reconfiguration of existing cobot cells for quality control purposes. In this paper, we discuss the testing of the CBQC system, together with creating a pattern database, training the ML model, and adding a predictive model to avoid defects in product cable sequence. Preliminary testing is carried out in the laboratory environment which leads to production testing in SME manufacturing. Results, developments, and future work will be presented at the end of the paper.
EN
The successful selection process of industrial robots (IRs) for today’s Cyber-Physical Systems is an important topic and there are different possibilities to solve the task. The primary task is to estimate the existing IR selection systems according to the suitability analysis and to highlight the main positive features and problematic areas. The objective of the reverse task is to carry out the sensitivity analysis of the existing robot-based manufacturing systems. The matching of these two approaches helps decision makers to develop the main principles of IR selection in today’s multidimensional and fast-changing economic world.
EN
Standardized and universal solutions for industrial robot integration are increasingly urgent requirements for companies looking for machine interconnectivity, and flexibility in creating tailor made manufacturing systems. These solutions must be supported by modular and open-source components able to easily integrate new control methods and advanced Extended Reality (XR) interfaces. Robot Operating System (ROS) has proven to be a reliable standard for industrial robot integration. ROS compatibility software is provided by many producers and allows for the implementation of modular control units by unifying development practices along the same libraries and methods. Digital Twins (DT) of industrial equipment and processes offer a solid base to develop innovative digital tools relying on synchronization between physical and digital entities and to easily setup intuitive XR interfaces for teleoperation and programming. This work presents the integration of the OMRON TM5-9000 collaborative industrial robot into the IVAR laboratory DT system at Tallinn University of Technology. By using Unity3D game engine and developing a ROS package for the specific machine, the digital model of the collaborative robot is integrated into the existing twin. Synchronization with the real counterpart is provided by MQTT protocol while a robot user interface is developed in Unity and provides robot joints visualization and remote control.
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