Search

Your search keyword '"Rudas, Imre J."' showing total 54,244 results
Start Over Author "Rudas, Imre J."

Refine your results

more »

more »

more »

more »
54,244 results on '"Rudas, Imre J."'

1. On the Philosophical, Cognitive and Mathematical Foundations of Symbiotic Autonomous Systems (SAS)

Author

Wang, Yingxu, Karray, Fakhri, Kwong, Sam, Plataniotis, Konstantinos N., Leung, Henry, Hou, Ming, Tunstel, Edward, Rudas, Imre J., Trajkovic, Ljiljana, Kaynak, Okyay, Kacprzyk, Janusz, Zhou, Mengchu, Smith, Michael H., Chen, Philip, and Patel, Shushma

Subjects
Computer Science - Artificial Intelligence
Abstract

Symbiotic Autonomous Systems (SAS) are advanced intelligent and cognitive systems exhibiting autonomous collective intelligence enabled by coherent symbiosis of human-machine interactions in hybrid societies. Basic research in the emerging field of SAS has triggered advanced general AI technologies functioning without human intervention or hybrid symbiotic systems synergizing humans and intelligent machines into coherent cognitive systems. This work presents a theoretical framework of SAS underpinned by the latest advances in intelligence, cognition, computer, and system sciences. SAS are characterized by the composition of autonomous and symbiotic systems that adopt bio-brain-social-inspired and heterogeneously synergized structures and autonomous behaviors. This paper explores their cognitive and mathematical foundations. The challenge to seamless human-machine interactions in a hybrid environment is addressed. SAS-based collective intelligence is explored in order to augment human capability by autonomous machine intelligence towards the next generation of general AI, autonomous computers, and trustworthy mission-critical intelligent systems. Emerging paradigms and engineering applications of SAS are elaborated via an autonomous knowledge learning system that symbiotically works between humans and cognitive robots., Comment: Accepted by Phil. Trans. Royal Society (A): Math, Phys & Engg Sci., 379(219x), 2021, Oxford, UK

Published
2021
Full Text
View/download PDF

3. Industrial and Medical Cyber-Physical Systems: Tackling User Requirements and Challenges in Robotics

Author

Haidegger, Tamás, Virk, Gurvinder S., Herman, Carol, Bostelman, Roger, Galambos, Péter, Györök, György, Rudas, Imre J., Rudas, Imre J., Series Editor, Szakál, Anikó, Series Editor, Batyrshin, Ildar, Editorial Board Member, Bokor, József, Editorial Board Member, De Baets, Bernard, Editorial Board Member, Fujita, Hamido, Editorial Board Member, Fukuda, Toshio, Editorial Board Member, Harashima, Fumio, Editorial Board Member, Hirota, Kaoru, Editorial Board Member, Pap, Endre, Editorial Board Member, Wilamowski, Bogdan M., Editorial Board Member, Baranyi, P., Advisory Editor, Bodenhofer, U., Advisory Editor, Fichtinger, G., Advisory Editor, Fullér, R., Advisory Editor, Galántai, A., Advisory Editor, Hluchý, L., Advisory Editor, Jamshidi, M. O., Advisory Editor, Kelemen, J., Advisory Editor, Kocur, D., Advisory Editor, Korondi, P., Advisory Editor, Kovács, G., Advisory Editor, Kóczy, L. T., Advisory Editor, Madarász, L., Advisory Editor, Nguyen, CH. C., Advisory Editor, Petriu, E., Advisory Editor, Precup, R.-E., Advisory Editor, Preitl, S., Advisory Editor, Prostean, O., Advisory Editor, Puri, V., Advisory Editor, Sallai, G. Y., Advisory Editor, Somló, J., Advisory Editor, Takács, M., Advisory Editor, Tar, J., Advisory Editor, Ungvari, L., Advisory Editor, Várkonyi-Kóczy, A. R., Advisory Editor, Várlaki, P., Advisory Editor, Vokorokos, L., Advisory Editor, Kovács, Levente, editor, and Haidegger, Tamás, editor

Published
2020
Full Text
View/download PDF

4. Sensor-Enhanced Smart Gripper Development for Automated Meat Processing.

Author

Takács, Kristóf, Takács, Bence, Garamvölgyi, Tivadar, Tarsoly, Sándor, Alexy, Márta, Móga, Kristóf, Rudas, Imre J., Galambos, Péter, and Haidegger, Tamás

Subjects
MECHATRONICS, ANIMAL diversity, MEAT industry, INTELLIGENT sensors, OBJECT manipulation, CYBER physical systems
Abstract

Grasping and object manipulation have been considered key domains of Cyber-Physical Systems (CPS) since the beginning of automation, as they are the most common interactions between systems, or a system and its environment. As the demand for automation is spreading to increasingly complex fields of industry, smart tools with sensors and internal decision-making become necessities. CPS, such as robots and smart autonomous machinery, have been introduced in the meat industry in recent decades; however, the natural diversity of animals, potential anatomical disorders and soft, slippery animal tissues require the use of a wide range of sensors, software and intelligent tools. This paper presents the development of a smart robotic gripper for deployment in the meat industry. A comprehensive review of the available robotic grippers employed in the sector is presented along with the relevant recent research projects. Based on the identified needs, a new mechatronic design and early development process of the smart gripper is described. The integrated force sensing method based on strain measurement and magnetic encoders is described, including the adjacent laboratory and on-site tests. Furthermore, a combined slip detection system is presented, which relies on an optical flow-based image processing algorithm using the video feed of a built-in endoscopic camera. Basic user tests and application assessments are presented. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

6. Strategies and Outcomes of Building a Successful University Research and Innovation Ecosystem

Author

Haidegger, Tamás P., primary, Galambos, Péter, additional, Tar, József K., additional, Kovács, Levente A., additional, Kozlovszky, Miklós, additional, Zrubka, Zsombor, additional, Eigner, György, additional, Drexler, Dániel A., additional, Szakál, Anikó, additional, Reicher, Viktória, additional, Árendás, Csaba, additional, Tarsoly, Sándor, additional, Garamvölgyi, Tivadar, additional, and Rudas, Imre J., additional

Published
2024
Full Text
View/download PDF

7. Elliptic problems on the ball endowed with Funk-type metrics

Author

Kristály, Alexandru and Rudas, Imre J.

Subjects
Mathematics - Analysis of PDEs
Abstract

We study Sobolev spaces on the $n-$dimensional unit ball $B^n(1)$ endowed with a parameter-depending Finsler metric $F_a$, $a\in [0,1],$ which interpolates between the Klein metric $(a=0)$ and Funk metric $(a=1)$, respectively. We show that the standard Sobolev space defined on the Finsler manifold $(B^n(1),F_a)$ is a vector space if and only if $a\in [0,1).$ Furthermore, by exploiting variational arguments, we provide non-existence and existence results for sublinear elliptic problems on $(B^n(1),F_a)$ involving the Finsler-Laplace operator whenever $a\in [0,1).$, Comment: 14 pages

Published
2014

10. Towards Real-Time Łukasiewicz Fuzzy Systems

Author

Bede, Barnabas, Rudas, Imre J., Kacprzyk, Janusz, Series Editor, Zadeh, Lotfi A., editor, Yager, Ronald R., editor, Shahbazova, Shahnaz N., editor, Reformat, Marek Z., editor, and Kreinovich, Vladik, editor

Published
2018
Full Text
View/download PDF

19. Human Body Thermal Atlas

Author

Živčák, Jozef, Madarász, Ladislav, Hudák, Radovan, Rudas, Imre J., Živčák, Jozef, Hudák, Radovan, Madarász, Ladislav, and Rudas, Imre J.

Published
2013
Full Text
View/download PDF

24. Thermographic Diagnostics

Author

Živčák, Jozef, Madarász, Ladislav, Hudák, Radovan, Rudas, Imre J., Živčák, Jozef, Hudák, Radovan, Madarász, Ladislav, and Rudas, Imre J.

Published
2013
Full Text
View/download PDF

25. Infrared Thermography

Author

Živčák, Jozef, Madarász, Ladislav, Hudák, Radovan, Rudas, Imre J., Živčák, Jozef, Hudák, Radovan, Madarász, Ladislav, and Rudas, Imre J.

Published
2013
Full Text
View/download PDF

29. Request Driven Generation of RFLP Elements at Product Definition

Author

Horváth, László, Rudas, Imre J., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Moreno-Díaz, Roberto, editor, Pichler, Franz, editor, and Quesada-Arencibia, Alexis, editor

Published
2015
Full Text
View/download PDF

43. Event-Triggered Control for Networked Lurie Control Systems Subject to Periodic Denial-of-Service Attacks and Time Delays

Author

Wang, Yanfeng, He, Ping, Shi, Peng, and Rudas, Imre J.

Abstract

A controller design method based on an event-triggered mechanism for networked Lurie control systems subject to periodic denial-of-service (DoS) attacks and time delays is proposed in this article. First, an observer is constructed for the case where the system state is unavailable. According to the impact of periodic DoS attack signal and time delays, the networked Lurie control system is modeled as a switched system composed of two subsystems. Second, according to Lyapunov theory, the absolute exponential stability conditions of the system are derived, and the relationship among the system sampling period, time delays, attack (sleeping) period, and the closed-loop system decay rate is obtained. Third, the joint design method of the controller, the observer, and the event-triggered mechanism is given. Finally, an example is used to verify the effectiveness of the obtained results.

Published
2024
Full Text
View/download PDF

44. Adaptive Extended State Observer-Based Velocity-Free Servo Tracking Control With Friction Compensation

Author

Lin, Weiyang, Zhang, Zhongjin, Yu, Xinghu, Qiu, Jianbin, Rudas, Imre J., Gao, Huijun, and Qu, Dongsheng

Abstract

In this article, a velocity-free adaptive controller is proposed for the tracking control of servo mechanisms with friction compensation. A continuously differentiable friction model is employed to compensate for the dominant friction nonlinearity of servo mechanisms. Besides, a projection-type adaptive law is applied to handle parameter uncertainties in the system model. Since only the output position signal is directly measurable, an adaptive extended state observer (AESO) is constructed to estimate the indeterminate velocity state, which can also provide an estimation of unmodeled dynamics. Moreover, the dynamic gain switching of AESO can effectively suppress the peaking phenomenon at the motion beginning. Specifically, the parameter adaptation law utilizes the desired velocity state instead of the estimated value, avoiding the coupling problem between parameter and state estimation. The proposed control strategy theoretically demonstrates the transient performance and boundedness of the error in output tracking. Asymptotic stabilization of the system can also be implemented when only parameter uncertainty exists. Comparative experiments are conducted on a linear motor platform to demonstrate the effectiveness of the proposed control scheme.

Published
2024
Full Text
View/download PDF

45. Increasing the Robustness of Deep Learning Models for Object Segmentation: A Framework for Blending Automatically Annotated Real and Synthetic Data

Author

Karoly, Artur Istvan, Tirczka, Sebestyen, Gao, Huijun, Rudas, Imre J., and Galambos, Peter

Abstract

Recent problems in robotics can sometimes only be tackled using machine learning technologies, particularly those that utilize deep learning (DL) with transfer learning. Transfer learning takes advantage of pretrained models, which are later fine-tuned using smaller task-specific datasets. The fine-tuned models must be robust against changes in environmental factors such as illumination since, often, there is no guarantee for them to be constant. Although synthetic data for pretraining has been shown to enhance DL model generalization, there is limited research on its application for fine-tuning. One limiting factor is that the generation and annotation of synthetic datasets can be cumbersome and impractical for the purpose of fine-tuning. To address this issue, we propose two methods for automatically generating annotated image datasets for object segmentation, one for real-world and another for synthetic images. We also introduce a novel domain adaptation approach called filling the reality gap (FTRG), which can blend elements from real-world and synthetic scenes in a single image to achieve domain adaptation. We demonstrate through experimentation on a representative robot application that FTRG outperforms other domain adaptation techniques, such as domain randomization or photorealistic synthetic images, in creating robust models. Furthermore, we evaluate the benefits of using synthetic data for fine-tuning in transfer learning and continual learning with experience replay using our proposed methods and FTRG. Our findings indicate that fine-tuning with synthetic data can produce superior results compared to solely using real-world data.

Published
2024
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results