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"Robots, Industrial"
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Teleoperation of industrial robot manipulators based on augmented reality
This research develops a novel teleoperation for robot manipulators based on augmented reality. The proposed interface is equipped with full capabilities in order to replace the classical teach pendant of the robot for carrying out teleoperation tasks. The proposed interface is based on an augmented reality headset for projecting computer-generated graphics onto the real environment and a gamepad to interact with the computer-generated graphics and provide robot commands. In order to demonstrate the benefits of the proposed method, several usability tests were conducted using a 6R industrial robot manipulator in order to compare the proposed interface and the conventional teach pendant interface for teleoperation tasks. In particular, the results of these usability tests show that the proposed approach is more intuitive, ergonomic, and easy to use. Furthermore, the comparison results also show that the proposed method clearly improves the velocity of the teleoperation task, regardless of the user’s previous experience in robotics and augmented reality technology.
Journal Article
Robots at work
\"Robots are machines that can do work on their own. Read about all of the different and exciting jobs robots do in our communities\"-- Provided by publisher.
Book
Hybrid BW-EDAS MCDM methodology for optimal industrial robot selection
Industrial robots have different capabilities and specifications according to the required applications. It is becoming difficult to select a suitable robot for specific applications and requirements due to the availability of several types with different specifications of robots in the market. Best-worst method is a useful, highly consistent and reliable method to derive weights of criteria and it is worthy to integrate it with the evaluation based on distance from average solution (EDAS) method that is more applicable and needs fewer number of calculations as compared to other methods. An example is presented to show the validity and usability of the proposed methodology. Comparison of ranking results matches with the well-known distance-based approach, technique for order preference by similarity to ideal solution and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methods showing the robustness of the best-worst EDAS hybrid method. Sensitivity analysis performed using eighty to one ratio shows that the proposed hybrid MCDM methodology is more stable and reliable.
Journal Article
Factory robots
\"A photo-illustrated book for elementary readers about robots that work to make and package our goods. Describes the technological history that led to today's automated assembly machines. Explains their role today and possible future applications. Includes Q&A feature, glossary, index, and further resources\"-- Provided by publisher.
Book
S-Curve Trajectory Planning for Industrial Robots Based on Curvature Radius
Motion planning in robotic systems, particularly in industrial contexts, must balance execution speed, precision, and safety. Excessive accelerations, especially centripetal ones in high, curvature regions, can cause vibrations, reduce tracking accuracy, and increase mechanical wear. This paper presents an off-line motion planning method that integrates curvature-based velocity modulation with jerk- and acceleration-limited S-curve profiles. The approach autonomously adjusts the speed along a predefined path according to local curvature by planning the motion at piecewise constant velocity and ensuring compliance with dynamic constraints on jerk, acceleration, and velocity. A non-linear filter tracks the velocity reference and smooths transitions while maintaining fluid motion, automatically adjusting velocity based on path curvature, ensuring smooth S-curve trajectories without requiring manual intervention. By jointly addressing geometric feasibility and dynamic smoothness, the proposed method reduces execution time while minimizing vibrations in applications involving abrupt curvature variations, as confirmed by its application to planar and spatial trajectories with varying curvature complexity. The method applies to smooth parametric trajectories and is not intended for paths with tangent discontinuities. The simulation results confirm full compliance with the imposed acceleration and jerk limits; nevertheless, future work will include experimental validation on realistic process trajectories and a quantitative performance assessment.
Journal Article
Global perspectives on robotics and autonomous systems : development and applications
\"Global Perspectives on Robotics and Autonomous Systems: Development and Applications describes the evolution of robotics and autonomous systems, their development, their technologies, and their applications. This book discusses the concept of autonomy, requirements, and its role in shaping the behavior of these robots so that they can make their own effective and safe decisions and act on them reliably while assuring real-life requirements. Covering topics such as digital transformation, fused deposition modeling (FDM), and organizational unbundling process, this premier reference source is an essential resource for engineers, computer scientists, industry professionals, manufacturers, smart systems developers, data analysts, students and educators of higher educations, researchers, and academicians\"-- Provided by publisher.
BOOK
Autoencoder-based anomaly detection of industrial robot arm using stethoscope based internal sound sensor
Sound and vibration analysis are prominent tools for machine health diagnosis. Especially, neural network (NN) strategies have focused on finding complex and nonlinear relationships between the sensor signal and the machine status to detect machine faults. However, it is difficult to collect enough amount of fault data as much as normal status data for training general NN models. To resolve the issue, this paper proposes the autoencoder-based anomaly detection framework for industrial robot arms using an internal sound sensor. The autoencoder uses signals in the normal state of the robots for training the model. It reconstructs the input signals as output, and anomalous states are found from high reconstruction error. Two stethoscopes were attached to the surface of the robot joint as sensors, and the sounds were recorded by USB microphone attached to the outlet of the stethoscopes. Features were extracted from STFT spectrogram images of the gathered sound, then used to train and test an autoencoder model. The reconstruction errors of the autoencoder were compared to distinguish the abnormal status from normal one. The experimental results suggest that the stethoscopes prevent the interference of noise, and the collected sound signals can be utilized for detecting machine anomalies.
Journal Article
Work : a deep history, from the stone age to the age of robots
\"A revolutionary new history of humankind through the prism of work by leading anthropologist James Suzman\"-- Provided by publisher.
Industrial Robots in Mechanical Machining: Perspectives and Limitations
Recently, the need to produce from soft materials or components in extra-large sizes has appeared, requiring special solutions that are affordable using industrial robots. Industrial robots are suitable for such tasks due to their flexibility, accuracy, and consistency in machining operations. However, robot implementation faces some limitations, such as a huge variety of materials and tools, low adaptability to environmental changes, flexibility issues, a complicated tool path preparation process, and challenges in quality control. Industrial robotics applications include cutting, milling, drilling, and grinding procedures on various materials, including metal, plastics, and wood. Advanced robotics technologies involve the latest advances in robotics, including integrating sophisticated control systems, sensors, data fusion techniques, and machine learning algorithms. These innovations enable robots to adapt better and interact with their environment, ultimately increasing their accuracy. The main focus of this study is to cover the most common industrial robotic machining processes and to identify how specific advanced technologies can improve their performance. In most of the studied literature, the primary research objective across all operations is to enhance the stiffness of the robotic arm’s structure. Some publications propose approaches for planning the robot’s posture or tool orientation. In contrast, others focus on optimizing machining parameters through the utilization of advanced control and computation, including machine learning methods with the integration of collected sensor data.
Journal Article