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Journal articles on the topic 'Networked teleoperation'

Author: Grafiati
Published: 9 September 2022
Last updated: 19 July 2025

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1

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

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2

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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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

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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5

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

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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 (2014): 451–62. http://dx.doi.org/10.1017/s026357471400037x.

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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

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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8

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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9

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

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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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10

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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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 (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 (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 (2004): 1218–27. http://dx.doi.org/10.1109/tie.2004.837866.

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16

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 (2016): 1051–64. http://dx.doi.org/10.1109/tcyb.2015.2422785.

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17

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 (2014): 631–41. http://dx.doi.org/10.1109/tfuzz.2013.2269694.

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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

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

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20

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 (2019): 2706–17. http://dx.doi.org/10.1109/tmech.2019.2946197.

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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 (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 (2015): 2009–20. http://dx.doi.org/10.1109/tmech.2014.2359969.

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23

Gilerson, André, Niklas Bünte, Pierre E. Kehl, and Robert H. Schmitt. "Adaptive Control Strategies for Networked Systems: A Reinforcement Learning-Based Approach." Electronics 14, no. 7 (2025): 1312. https://doi.org/10.3390/electronics14071312.

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Advances in industrial 5G communication technologies and robotics create new possibilities while also increasing the complexity and variability of networked control systems. The additional throughput and lower latency provided by 5G networks enable applications such as teleoperation of machinery, flexible reconfigurable robotic manufacturing cells, or automated guided vehicles. These use cases are set up in dynamic network environments where communication latency and jitter become critical factors that must be managed. Despite the advancements in 5G technologies, such as ultra-reliable low-lat
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24

Xi, Lei, Haochen Zhang, Jianrong Liu, Wenxu Zhang, and Yangming Fan. "A Novel P + d Control Scheme for Time-Delayed Telerobotic Systems with Damping Adjustment." Processes 13, no. 3 (2025): 611. https://doi.org/10.3390/pr13030611.

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This paper presents a novel Proportional Damping Injection (P + d) control scheme that incorporates a damping regulation strategy and an adaptive method for networked telerobotic systems. Unlike the traditional P + d controller with a fixed damping coefficient, the proposed approach includes a dynamic damping adjuster, designed based on position error, to enhance the position tracking speed and improve the system robustness. To address uncertainties in dynamic models and external forces, Radial Basis Function (RBF) neural networks and an adaptive strategy are employed for dynamic estimation. T
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25

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 (2015): 67. http://dx.doi.org/10.15837/ijccc.2016.1.1577.

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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 prov
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26

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 slidin
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27

Yoshida, Kazuya, Kiyoshi Kiyokawa, Yashusi Yagi, et al. "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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28

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 (2008): 746–53. http://dx.doi.org/10.5391/jkiis.2008.18.6.746.

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29

Lim, Taeyoon, Myeonghwan Hwang, Eugene Kim, and Hyunrok Cha. "Authority Transfer According to a Driver Intervention Intention Considering Coexistence of Communication Delay." Computers 12, no. 11 (2023): 228. http://dx.doi.org/10.3390/computers12110228.

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Recently, interest and research on autonomous driving technology have been actively conducted. However, proving the safety of autonomous vehicles and commercializing autonomous vehicles remain key challenges. According to a report released by the California Department of Motor Vehicles on self-driving, it is still hard to say that self-driving technology is highly reliable. Until fully autonomous driving is realized, authority transfer to humans is necessary to ensure the safety of autonomous driving. Several technologies, such as teleoperation and haptic-based approaches, are being developed
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30

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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31

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

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32

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 (2013): 070506. http://dx.doi.org/10.1088/1674-1056/22/7/070506.

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33

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 (2017): 1–28. http://dx.doi.org/10.1145/3063594.

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34

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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35

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 (2021): 26. http://dx.doi.org/10.3390/mti5050026.

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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
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36

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

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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 opera
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37

LIU, DongYu, YueJiang HAN, DongZhe WANG, et al. "Review and prospects of orbit-to-surface teleoperation." SCIENTIA SINICA Technologica 50, no. 6 (2020): 716–28. http://dx.doi.org/10.1360/sst-2020-0120.

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38

Cahyadi, Adha Imam, Prapto Nugroho, and Yoshio Yamamoto. "Hybrid Design of Passive Mobile Robot Teleoperation System." ECTI Transactions on Electrical Engineering, Electronics, and Communications 8, no. 2 (2009): 232–38. http://dx.doi.org/10.37936/ecti-eec.201082.172109.

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This paper presents a preliminary design of remotely teleoperated vehicle such as mobile robot using haptic device. The perception principle of the slave side is constructed based on the classical Potential Field approach and especially used for detecting the presence of obstacles. A feedback linerization scheme is employed to render the mobile robot to be a passive system. As the interaction with the obstacle based on the potential ¯eld method is passive by nature, with additional assumption that the user is skilled, the connection between the haptic device andthe mobile robot is guaranteed t
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39

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

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40

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 (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 stre
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41

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 (2010): 450–62. http://dx.doi.org/10.1162/pres_a_00008.

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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 stri
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42

Saunier, Léa, Nicolas Hoffmann, Marius Preda, and Catalin Fetita. "Virtual Reality Interface Evaluation for Earthwork Teleoperation." Electronics 12, no. 19 (2023): 4151. http://dx.doi.org/10.3390/electronics12194151.

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Automation and robotics are destined to play a critical role in the Industry 4.0 revolution, as illustrated by the emergence of autonomous machinery in earthwork operations. Despite rapid progress, autonomous agents will always require human supervision to instruct their mission and to guaranty safety when unexpected problems arise. Traditional human supervision requires an operator to physically enter each machine at risk and manually take control. This approach is time-consuming and requires highly qualified personnel capable of operating various machines. This process can be hastened and si
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43

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

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44

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 (2022): 169–80. http://dx.doi.org/10.1109/thms.2022.3149167.

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45

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

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46

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 (2022): 157–68. http://dx.doi.org/10.1109/thms.2022.3142107.

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47

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 (2019): 32–46. http://dx.doi.org/10.1109/thms.2018.2878815.

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48

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 (2021): 34–40. http://dx.doi.org/10.1109/mcom.001.2000581.

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49

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 (2020): 773–95. http://dx.doi.org/10.1016/j.jfranklin.2019.04.001.

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50

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 (2019): 827–35. http://dx.doi.org/10.1007/s40998-019-00206-6.

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