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Статті в журналах з теми "Networked teleoperation"

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Автор: Grafiati

Опубліковано: 9 вересня 2022

Оновлено: 18 вересня 2022

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1

Hirche, S., P. Hinterseer, E. Steinbach, and M. Buss. "TOWARDS DEADBAND CONTROL IN NETWORKED TELEOPERATION SYSTEMS." IFAC Proceedings Volumes 38, no. 1 (2005): 70–75. http://dx.doi.org/10.3182/20050703-6-cz-1902.01414.

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2

Goldberg, K., D. Song, and A. Levandowski. "Collaborative teleoperation using networked spatial dynamic voting." Proceedings of the IEEE 91, no. 3 (March 2003): 430–39. http://dx.doi.org/10.1109/jproc.2003.809209.

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3

Yang, Xian, Changchun Hua, Jing Yan, and Xinping Guan. "New stability criteria for networked teleoperation system." Information Sciences 233 (June 2013): 244–54. http://dx.doi.org/10.1016/j.ins.2013.01.016.

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4

Polushin, Ilia G., and Sergey N. Dashkovskiy. "A Small Gain Framework for Networked Cooperative Teleoperation *." IFAC Proceedings Volumes 43, no. 14 (September 2010): 90–95. http://dx.doi.org/10.3182/20100901-3-it-2016.00240.

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5

Li, Jian-ning, Ya-Jun Pan, Trent Hilliard, and Hongye Su. "Robust Stochastic Control for Networked Bilateral Teleoperation Systems." IFAC Proceedings Volumes 46, no. 20 (2013): 112–17. http://dx.doi.org/10.3182/20130902-3-cn-3020.00028.

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6

Yang, Yana, Changchun Hua, Huafeng Ding, and Xinping Guan. "Finite-time coordination control for networked bilateral teleoperation." Robotica 33, no. 2 (March 5, 2014): 451–62. http://dx.doi.org/10.1017/s026357471400037x.

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Анотація:

SUMMARYA continuous finite-time control scheme for networked bilateral teleoperation is proposed in this brief. The terminal sliding mode technology is used and new master–slave torques are designed. With the new controller, the coordination error of the master manipulator and the slave manipulator converges to zero in finite time. Moreover, the reaching time and the sliding time can be derived. Finally, the comparisons are performed and simulations show the effectiveness of the proposed approach.

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7

Takahashi, M., H. Urabe, and Y. Kunii. "Teleoperation System by using Networked Dynamic Force Simulator." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2003 (2003): 131. http://dx.doi.org/10.1299/jsmermd.2003.131_6.

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8

Kristalny, Maxim, and Jang Ho Cho. "Admittance parameterization in linear networked bilateral teleoperation control." Automatica 124 (February 2021): 109357. http://dx.doi.org/10.1016/j.automatica.2020.109357.

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9

Mori, Taketoshi. "From Telerobotics to Networked Robotics. Object-Oriented Teleoperation System." Journal of the Robotics Society of Japan 17, no. 4 (1999): 467–72. http://dx.doi.org/10.7210/jrsj.17.467.

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10

Zhang, Xian-Ming. "Recent Developments in Time-Delay Systems and Their Applications." Electronics 8, no. 5 (May 17, 2019): 552. http://dx.doi.org/10.3390/electronics8050552.

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Анотація:

The last few decades have witnessed the rapid development of networked control systems due to their significant advantages and they have been applied to variant industrial areas such as unmanned surface vehicles, unmanned space vehicles, smart grids, wastewater treatment processes, Internet-based teleoperation, intelligent transportation systems and so on [...]

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11

Hara, Isao. "From Telerobotics to Networked Robotics. Teleoperation System on the Ineternet." Journal of the Robotics Society of Japan 17, no. 4 (1999): 477–80. http://dx.doi.org/10.7210/jrsj.17.477.

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12

Matsumaru, Takafumi. "From Telerobotics to Networked Robotics. Teleoperation Through ISDN Communication Network." Journal of the Robotics Society of Japan 17, no. 4 (1999): 481–85. http://dx.doi.org/10.7210/jrsj.17.481.

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13

Polushin, Ilia G., Sergey N. Dashkovskiy, Amir Takhmar, and Rajni V. Patel. "A small gain framework for networked cooperative force-reflecting teleoperation." Automatica 49, no. 2 (February 2013): 338–48. http://dx.doi.org/10.1016/j.automatica.2012.11.001.

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14

Tipsuwan, Y., and M. Y. Chow. "Gain Scheduler Middleware: A Methodology to Enable Existing Controllers for Networked Control and Teleoperation—Part II: Teleoperation." IEEE Transactions on Industrial Electronics 51, no. 6 (December 2004): 1228–37. http://dx.doi.org/10.1109/tie.2004.837865.

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15

Tipsuwan, Y., and M. Y. Chow. "Gain Scheduler Middleware: A Methodology to Enable Existing Controllers for Networked Control and Teleoperation—Part I: Networked Control." IEEE Transactions on Industrial Electronics 51, no. 6 (December 2004): 1218–27. http://dx.doi.org/10.1109/tie.2004.837866.

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16

Yang, Yana, Changchun Hua, and Xinping Guan. "Adaptive Fuzzy Finite-Time Coordination Control for Networked Nonlinear Bilateral Teleoperation System." IEEE Transactions on Fuzzy Systems 22, no. 3 (June 2014): 631–41. http://dx.doi.org/10.1109/tfuzz.2013.2269694.

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17

Li, Zhijun, Yuanqing Xia, Dehong Wang, Di-Hua Zhai, Chun-Yi Su, and Xingang Zhao. "Neural Network-Based Control of Networked Trilateral Teleoperation With Geometrically Unknown Constraints." IEEE Transactions on Cybernetics 46, no. 5 (May 2016): 1051–64. http://dx.doi.org/10.1109/tcyb.2015.2422785.

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18

Kosuge, Kazuhiro. "From Telerobotics to Networked Robotics. Teleoperation via Computer Network Using Environmental Predictive Display." Journal of the Robotics Society of Japan 17, no. 4 (1999): 473–76. http://dx.doi.org/10.7210/jrsj.17.473.

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19

Chen, Haifei, Panfeng Huang, and Zhengxiong Liu. "Mode Switching-Based Symmetric Predictive Control Mechanism for Networked Teleoperation Space Robot System." IEEE/ASME Transactions on Mechatronics 24, no. 6 (December 2019): 2706–17. http://dx.doi.org/10.1109/tmech.2019.2946197.

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20

Liu, Yen-Chen. "Robust synchronisation of networked Lagrangian systems and its applications to multi-robot teleoperation." IET Control Theory & Applications 9, no. 1 (January 2, 2015): 129–39. http://dx.doi.org/10.1049/iet-cta.2013.0914.

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21

Yang, Yana, Changchun Hua, and Xinping Guan. "Adaptive fuzzy synchronization control for networked teleoperation system with input and multi-state constraints." Journal of the Franklin Institute 353, no. 12 (August 2016): 2814–34. http://dx.doi.org/10.1016/j.jfranklin.2016.04.009.

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22

Hua, Changchun, Yana Yang, and Peter X. Liu. "Output-Feedback Adaptive Control of Networked Teleoperation System With Time-Varying Delay and Bounded Inputs." IEEE/ASME Transactions on Mechatronics 20, no. 5 (October 2015): 2009–20. http://dx.doi.org/10.1109/tmech.2014.2359969.

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23

Kuzu, Ahmet, Seta Bogosyan, and Metin Gokasan. "Predictive Input Delay Compensation with Grey Predictor for Networked Control System." International Journal of Computers Communications & Control 11, no. 1 (November 16, 2015): 67. http://dx.doi.org/10.15837/ijccc.2016.1.1577.

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Анотація:

The performance of networked control systems is affected strictly by time delay. Most of the literature in the area handle the problem from a stability perspective. However, stability optimized algorithms alone are not sufficient to reduce synchronization problems caused by time delay between the action and reaction in geographically distant places, and the effect and performance of other system components should also be taken into account. In teleoperation applications the reference is often provided by a human, known as the operator, and due to the nature of the human system, references provided by the human operator are of a much lower bandwidth when compared to common control reference inputs. This paper focuses on the operator, and proposes an approach to predict the manipulator’s motion (created by the operator) ahead of time with an aim to reduce the time delay between the master and slave manipulator trajectories. To highlight the improvement offered by the developed approach, hereby called Predictive Input Delay Compensator (PIDC), we compare the performance with the only other study in the literature that handles this problem using the Taylor Series approach. The performance of these two approaches is evaluated experimentally for the forward (control) path on a PUMA robot, manipulated by a human operator and it has been demonstrated that the efficient latency in the forward path is decreased by 100ms, on average, reducing the forward latency from 350ms to 250ms.

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24

Kuzu, Ahmet, Seta Bogosyan, Metin Gokasan, and Asif Sabanovic. "Experimental Evaluation of Novel Master-Slave Configurations for Position Control under Random Network Delay and Variable Load for Teleoperation." Mathematical Problems in Engineering 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/608208.

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This paper proposes two novel master-slave configurations that provide improvements in both control and communication aspects of teleoperation systems to achieve an overall improved performance in position control. The proposed novel master-slave configurations integrate modular control and communication approaches, consisting of a delay regulator to address problems related to variable network delay common to such systems, and a model tracking control that runs on the slave side for the compensation of uncertainties and model mismatch on the slave side. One of the configurations uses a sliding mode observer and the other one uses a modified Smith predictor scheme on the master side to ensure position transparency between the master and slave, while reference tracking of the slave is ensured by a proportional-differentiator type controller in both configurations. Experiments conducted for the networked position control of a single-link arm under system uncertainties and randomly varying network delays demonstrate significant performance improvements with both configurations over the past literature.

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25

Yoshida, Kazuya, Kiyoshi Kiyokawa, Yashusi Yagi, Tadashi Adachi, Hiroaki Saitoh, Hiroyuki Tanaka, and Hiroyuki Ohno. "2A1-S-035 Development of a Networked Robotic System for Disaster Mitigation : Teleoperation of a Mobile Robot Through the Internet(Network/Media Robotics 2,Mega-Integration in Robotics and Mechatronics to Assist Our Daily Lives)." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2005 (2005): 170. http://dx.doi.org/10.1299/jsmermd.2005.170_4.

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26

Jin, Tae-Seok, and Hyun-Sik Kim. "Teleoperatoin System Control using a Robust State Estimation in Networked Environment." Journal of Korean Institute of Intelligent Systems 18, no. 6 (December 25, 2008): 746–53. http://dx.doi.org/10.5391/jkiis.2008.18.6.746.

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27

Rakkiyappan, R., B. Kaviarasan, and Ju H. Park. "Leader-following consensus for networked multi-teleoperator systems via stochastic sampled-data control." Neurocomputing 164 (September 2015): 272–80. http://dx.doi.org/10.1016/j.neucom.2015.02.060.

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28

Hoff, William A., Lance B. Gatrell, and John R. Spofford. "Machine-vision-based teleoperation aid." Telematics and Informatics 8, no. 4 (January 1991): 403–23. http://dx.doi.org/10.1016/s0736-5853(05)80062-0.

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29

Cizmeci, Burak, Xiao Xu, Rahul Chaudhari, Christoph Bachhuber, Nicolas Alt, and Eckehard Steinbach. "A Multiplexing Scheme for Multimodal Teleoperation." ACM Transactions on Multimedia Computing, Communications, and Applications 13, no. 2 (May 5, 2017): 1–28. http://dx.doi.org/10.1145/3063594.

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30

Park, M. J., S. M. Lee, J. W. Son, O. M. Kwon, and E. J. Cha. "Leader—following consensus control for networked multi-teleoperator systems with interval time-varying communication delays." Chinese Physics B 22, no. 7 (July 2013): 070506. http://dx.doi.org/10.1088/1674-1056/22/7/070506.

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31

KANNO, Takahiro, and Yasuyoshi YOKOKOHJI. "2P1-I06 Controller Design and Experimental System Development of A Networked Multi-User Teleoperator(Network Robotics)." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2011 (2011): _2P1—I06_1—_2P1—I06_4. http://dx.doi.org/10.1299/jsmermd.2011._2p1-i06_1.

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32

Kettwich, Carmen, Andreas Schrank, and Michael Oehl. "Teleoperation of Highly Automated Vehicles in Public Transport: User-Centered Design of a Human-Machine Interface for Remote-Operation and Its Expert Usability Evaluation." Multimodal Technologies and Interaction 5, no. 5 (May 5, 2021): 26. http://dx.doi.org/10.3390/mti5050026.

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Анотація:

Paving the way to future mobility, teleoperation of vehicles promises a reachable solution to effectively use the benefits of automated driving as long as fully automated vehicles (SAE 5) are not entirely feasible. Safety and reliability are assured by a human operator who remotely observes the vehicle and takes over control in cases of disturbances that exceed the vehicle automation’s skills. In order to integrate the vehicle’s automation and human remote-operation, we developed a novel user-centered human-machine interface (HMI) for teleoperation. It is tailored to the remote-operation of a highly automated shuttle (SAE 4) by a public transport control center and based on a systematic analysis of scenarios, of which detailed requirements were derived. Subsequently, a paper-pencil prototype was generated and refined until a click-dummy emerged. This click-dummy was evaluated by twelve control center professionals. The experts were presented the prototype in regular mode and were then asked to solve three scenarios with disturbances in the system. Using structured interview and questionnaire methodology, the prototype was evaluated regarding its usability, situation awareness, acceptance, and perceived workload. Results support our HMI design for teleoperation of a highly automated shuttle, especially regarding usability, acceptance, and workload. Participant ratings and comments indicated particularly high satisfaction with the interaction design to resolve disturbances and the presentation of camera images. Participants’ feedbacks provide valuable information for a refined HMI design as well as for further research.

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33

Nakayama, Angelica, Daniel Ruelas, Jesus Savage, and Ernesto Bribiesca. "Teleoperated Service Robot with an Immersive Mixed Reality Interface." Informatics and Automation 20, no. 6 (September 10, 2021): 1187–223. http://dx.doi.org/10.15622/ia.20.6.1.

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Анотація:

Teleoperated service robots can perform more complex and precise tasks as they combine robot skills and human expertise. Communication between the operator and the robot is essential for remote operation and strongly affects system efficiency. Immersive interfaces are being used to enhance teleoperation experience. However, latency or time delay can impair the performance of the robot operation. Since remote visualization involves transmitting a large amount of video data, the challenge is to decrease communication instability. Then, an efficient teleoperation system must have a suitable operation interface capable of visualizing the remote environment, controlling the robot, and having a fast response time. This work presents the development of a service robot teleoperation system with an immersive mixed reality operation interface where the operator can visualize the real remote environment or a virtual 3D environment representing it. The virtual environment aims to reduce the latency on communication by reducing the amount of information sent over the network and improve user experience. The robot can perform navigation and simple tasks autonomously or change to the teleoperated mode for more complex tasks. The system was developed using ROS, UNITY 3D, and sockets to be exported with ease to different platforms. The experiments suggest that having an immersive operation interface provides improved usability for the operator. The latency appears to improve when using the virtual environment. The user experience seems to benefit from the use of mixed reality techniques; this may lead to the broader use of teleoperated service robot systems.

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34

LIU, DongYu, YueJiang HAN, DongZhe WANG, Wei WANG, YunPeng LI, LiXian ZHANG, and GuangZhou XIAO. "Review and prospects of orbit-to-surface teleoperation." SCIENTIA SINICA Technologica 50, no. 6 (May 27, 2020): 716–28. http://dx.doi.org/10.1360/sst-2020-0120.

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35

Sgouros, Nikitas M., and Stelios Gerogiannakis. "Robot teleoperation environments featuring WAP-based wireless devices." Journal of Network and Computer Applications 26, no. 3 (January 2003): 259–71. http://dx.doi.org/10.1016/s1084-8045(03)00017-1.

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36

Cha, Jongeun, Julius Kammerl, and Abdulmotaleb El Saddik. "Improving Spatial Perception in Telepresence and Teleaction Systems by Displaying Distance Information through Visual and Vibrotactile Feedback." Presence: Teleoperators and Virtual Environments 19, no. 5 (October 1, 2010): 430–49. http://dx.doi.org/10.1162/pres_a_00006.

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Telepresence and teleaction (TPTA) systems enable humans to operate in a remote, hostile, or inaccessible environment. The performance of these systems strongly depends on the deployed sensors and actuators and the quality of the feedback to the user. Spatial perception plays an especially important role when handling dangerous and fragile objects. Stereoscopic cameras and displays can be deployed to improve spatial perception. However, in networked TPTA scenarios with limited transmission capacity on the communication link, the additional bandwidth required for sending two separate video streams is often infeasible. Furthermore, stereoscopic displays are known to have limitations in quality that affect spatial orientation when navigating within the remote environment. In this work, we present methods for displaying remotely measured distance between a teleoperator and a target object through visual and vibrotactile displays in order to improve spatial perception in TPTA systems. Furthermore, we propose to exploit human sensory illusions of the vibrotactile sense to overcome limitations of vibrotactile displays. Psychophysical experiments are conducted to investigate the performance of our proposed display methods. Our experiments show that our proposed vibrotactile feedback methods can compete with visual distance displays.

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37

Kammerl, Julius, Iason Vittorias, Verena Nitsch, Eckehard Steinbach, and Sandra Hirche. "Perception-Based Data Reduction for Haptic Force-Feedback Signals Using Velocity-Adaptive Deadbands." Presence: Teleoperators and Virtual Environments 19, no. 5 (October 1, 2010): 450–62. http://dx.doi.org/10.1162/pres_a_00008.

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Анотація:

In telepresence and teleaction (TPTA) systems, the transmission of haptic signals puts high demands on the applied signal processing and communication procedures. When running a TPTA session across a packet-based communication network (e.g., the Internet), minimizing the end-to-end delay results in packet rates of up to the applied sampling rate of the local control loops at the human system interface and the teleoperator. The perceptual deadband data reduction approach for haptic signals successfully addresses the challenge of high packet rates in networked TPTA systems and satisfies the strict delay constraints. In this paper, we extend the underlying perceptual model of the deadband approach by incorporating psychophysical findings on human force-feedback discrimination during operators' relative hand movements. By applying velocity-dependent perception thresholds to the deadband approach, we observe further improvement in efficiency and performance due to improved adaption to human haptic perception thresholds. The psychophysical experiments conducted reveal improved data reduction performance of our proposed haptic perceptual coding scheme without impairing the user experience. Our results show a high data reduction ability of up to 96% without affecting system transparency or the operator's task performance.

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38

Clarke, Stella, Gerhard Schillhuber, Michael F. Zaeh, and Heinz Ulbrich. "Prediction-based methods for teleoperation across delayed networks." Multimedia Systems 13, no. 4 (October 16, 2007): 253–61. http://dx.doi.org/10.1007/s00530-007-0103-z.

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39

Gholami, Soheil, Marta Lorenzini, Elena De Momi, and Arash Ajoudani. "Quantitative Physical Ergonomics Assessment of Teleoperation Interfaces." IEEE Transactions on Human-Machine Systems 52, no. 2 (April 2022): 169–80. http://dx.doi.org/10.1109/thms.2022.3149167.

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40

Estrada, Edgar, Wen Yu, and Xiaoou Li. "Stable bilateral teleoperation with phase transition and haptic feedback." Journal of the Franklin Institute 358, no. 3 (February 2021): 1940–56. http://dx.doi.org/10.1016/j.jfranklin.2020.12.027.

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41

Courtois, Hugo, Nabil Aouf, Kenan Ahiska, and Marco Cecotti. "OAST: Obstacle Avoidance System for Teleoperation of UAVs." IEEE Transactions on Human-Machine Systems 52, no. 2 (April 2022): 157–68. http://dx.doi.org/10.1109/thms.2022.3142107.

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42

Kebria, Parham M., Hamid Abdi, Mohsen Moradi Dalvand, Abbas Khosravi, and Saeid Nahavandi. "Control Methods for Internet-Based Teleoperation Systems: A Review." IEEE Transactions on Human-Machine Systems 49, no. 1 (February 2019): 32–46. http://dx.doi.org/10.1109/thms.2018.2878815.

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43

Hu, Fenghe, Yansha Deng, Hui Zhou, Tae Hun Jung, Chan-Byoung Chae, and A. Hamid Aghvami. "A Vision of an XR-Aided Teleoperation System toward 5G/B5G." IEEE Communications Magazine 59, no. 1 (January 2021): 34–40. http://dx.doi.org/10.1109/mcom.001.2000581.

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44

Li, Yuling, Yixin Yin, Sen Zhang, Jie Dong, and Rolf Johansson. "Composite adaptive control for bilateral teleoperation systems without persistency of excitation." Journal of the Franklin Institute 357, no. 2 (January 2020): 773–95. http://dx.doi.org/10.1016/j.jfranklin.2019.04.001.

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45

Mohammadi, Leila, and Alireza Alfi. "Guaranteed Cost Control in Delayed Teleoperation Systems Under Actuator Saturation." Iranian Journal of Science and Technology, Transactions of Electrical Engineering 43, no. 4 (May 9, 2019): 827–35. http://dx.doi.org/10.1007/s40998-019-00206-6.

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46

Nisky, Ilana, Ferdinando A. Mussa-Ivaldi, and Amir Karniel. "Analytical Study of Perceptual and Motor Transparency in Bilateral Teleoperation." IEEE Transactions on Human-Machine Systems 43, no. 6 (November 2013): 570–82. http://dx.doi.org/10.1109/tsmc.2013.2284487.

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47

Hua, Changchun, Yilu Wang, Yana Yang, and Xinping Guan. "Force feedback control for bilateral teleoperation system with unknown Prandtl-Ishlinskii hysteresis." Journal of the Franklin Institute 357, no. 13 (September 2020): 8321–41. http://dx.doi.org/10.1016/j.jfranklin.2020.03.001.

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48

LIU, ChuanKai, Jian LI, TianZhu ZHANG, Qian LIU, ZeYuan HUANG, JiTao ZHANG, YuHui GAO, et al. "Key technologies in the teleoperation of the Chang’e-5 lunar sampling." SCIENTIA SINICA Technologica 52, no. 3 (December 30, 2021): 473–88. http://dx.doi.org/10.1360/sst-2021-0271.

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