Effects of Visual Interface Design, and Control Mode and Latency on Performance, Telepresence and Workload in a Teleoperation Task
Abstract
Human-machine interfaces that facilitate telepresence are speculated to improve performance with teleoperators. Unfortunately, there is little experimental evidence to substantiate a direct link between the two. Further, there are limited data available on technological and psychological factors that affect telepresence. The objective of the present study was to evaluate the influence of interface design configuration, and control mode and latency on teleoperation performance, telepresence, and workload in a pick-and-place task. It was conducted to enhance understanding of the concept of telepresence and promote future development of telepresence-based guidelines for teleoperator systems. An experiment was conducted in which subjects were required to control a telerobot in a simple pick-and-place task through a virtual reality (VR) interface with or without live-video feedback on the motion of the robot. Rotational or translational motion control of the robot was studied under four control latencies ranging from 0 to 4 seconds. Results demonstrated significant benefits of using VR in conjunction with video feedback to control the telerobot. Rotational control appeared to better meet user expectations of robot motion control than modes involving translations of joint positions. Performance with the VR interface without live video feedback appeared to be sensitive to control latency. Correlation analysis provided further evidence of a positive link between telepresence and performance.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the dialoging mode of HIC, delays and reliability of haptic data communication are paramount for safe communication, with a latency requirement of 0-50 ms.
“In the dialoging mode, where the interaction is highly dynamic (e.g., therapist-patient interaction, where the therapist remotely operates a local robotic avatar to assist the local patient to perform rehabilitation exercises), delays and reliability of haptic data communication are paramount for safe communication (a latency requirement of 0-50 ms).”
From The IEEE 1918.1 “Tactile Internet” Standards Working Group and its Standards (2019) · cites this paper as [27]
For the observing mode of HIC, the latency requirement can be further extended to 0-200 ms.
“For the observing mode, where interaction is static or quasi-static (e.g., teletraining system, where a trainee will be observing the performance of a remote trainer), the latency requirement can be further extended to 0-200 ms.”
From The IEEE 1918.1 “Tactile Internet” Standards Working Group and its Standards (2019) · cites this paper as [27]
Cites
Musings on Telepresence and Virtual Presence
Sheridan, T. B. (1992) · Presence: Teleoperators and Virtual Environments · doi:10.1162/pres.1992.1.1.120 · Cited by 1,344 · cited 1× · see citing works
“Sheridan (1992) identified the ability to modify the remote environment as a major determinant of t&presence experiences.”
BackgroundA Quantitative Measure of Telepresence
Schloerb, D. W. (1995) · Presence - Teleoperators and Virtual Environments · doi:10.1162/pres.1995.4.1.64 · Cited by 311 · see citing works
Measuring Presence in Virtual Environments
Witmer, B. G., & Singer, M. F. (1994) · doi:10.21236/ada286183 · Cited by 95 · see citing works
Speculations on the Value of Telepresence
Draper, J. V., KABER, D. B., & Usher, J. M. (1999) · CyberPsychology & Behavior · doi:10.1089/cpb.1999.2.349 · Cited by 42 · see citing works
Self-citationRiley, J. M., & KABER, D. B. (1999) · PsycEXTRA Dataset · doi:10.1037/e575812012-018 · Cited by 2 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Common metrics for human-robot interaction
Steinfeld, A. M., Fong, T., KABER, D. B., Lewis, M., Scholtz, J. C., Schultz, A. C., & Goodrich, M. A. (2006) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/1121241.1121249 · Cited by 771 · see citing works
Self-citationHuman Performance Issues and User Interface Design for Teleoperated Robots
Chen, J. Y. C., Haas, E. C., & Barnes, M. J. (2007) · IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews) · doi:10.1109/tsmcc.2007.905819 · Cited by 646 · see citing works
A survey of environment-, operator-, and task-adapted controllers for teleoperation systems
Passenberg, C., Peer, A., & BUSS, M. J. (2010) · Mechatronics · doi:10.1016/j.mechatronics.2010.04.005 · Cited by 210 · see citing works
The IEEE 1918.1 “Tactile Internet” Standards Working Group and its Standards
Holland, O., Steinbach, E., Prasad, R. V., Liu, Q., Dawy, Z., Aijaz, A., Pappas, N., Chandra, K., Rao, V. S., Oteafy, S., et al. (2019) · Proceedings of the IEEE · doi:10.1109/jproc.2018.2885541 · Cited by 200 · see citing works
Riley, J. M., KABER, D. B., & Draper, J. V. (2003) · Human Factors and Ergonomics in Manufacturing & Service Industries · doi:10.1002/hfm.10050 · Cited by 78 · see citing works
Self-citationEye-Tracking for Performance Evaluation and Workload Estimation in Space Telerobotic Training
Guo, Y., Freer, D., Deligianni, F., & Yang, G. (2021) · IEEE Transactions on Human-Machine Systems · doi:10.1109/thms.2021.3107519 · Cited by 65 · see citing works
Lee, S., & Kim, G. J. (2008) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2008.05.001 · Cited by 63 · see citing works
Presence, workload and performance effects of synthetic environment design factors
Ma, R., & KABER, D. B. (2006) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2005.12.003 · Cited by 60 · see citing works
Self-citationYang, E., & Dorneich, M. C. (2017) · International Journal of Social Robotics · doi:10.1007/s12369-017-0407-x · Cited by 52 · see citing works
Lu, S., Zhang, M. Y., Ersal, T., & Yang, X. J. (2019) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2019.1574059 · Cited by 50 · see citing works
Multiple robot / single human interaction: effects on perceived workload
Adams, J. A. (2008) · Behaviour and Information Technology · doi:10.1080/01449290701288791 · Cited by 50 · see citing works
Wang, Z., Reed, I. J., & Fey, A. M. (2018) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2018.8460729 · Cited by 42 · see citing works
Kaber, D. B., Li, Y., Clamann, M., & Lee, Y.-S. (2012) · IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans · doi:10.1109/tsmca.2012.2201466 · Cited by 37 · see citing works
Self-citationKia, K., Hwang, J., Kim, I.-S., Ishak, H., & Kim, J. H. (2021) · Applied Ergonomics · doi:10.1016/j.apergo.2021.103502 · Cited by 37 · see citing works
The Underpinnings of Workload in Unmanned Vehicle Systems
Hooey, B. L., KABER, D. B., Adams, J. A., Fong, T., & Gore, B. F. (2017) · IEEE Transactions on Human-Machine Systems · doi:10.1109/thms.2017.2759758 · Cited by 37 · see citing works
Self-citationGatsoulis, Y., VIRK, G. S., & Dehghani-Sanij, A. A. (2010) · Journal of Cognitive Engineering and Decision Making · doi:10.1518/155534310x495591 · Cited by 37 · see citing works
Perception of Delay in Haptic Telepresence Systems
Rank, M., Shi, Z., & Hirche, S. (2010) · PRESENCE Virtual and Augmented Reality · doi:10.1162/pres_a_00021 · Cited by 36 · see citing works
Experimental Performance Analysis of a Homotopy-Based Shared Autonomy Framework
Anderson, S. J., Walker, J. M., & Iagnemma, K. D. (2014) · IEEE Transactions on Human-Machine Systems · doi:10.1109/tsmc.2014.2298383 · Cited by 33 · see citing works
Control gain adaptation in virtual reality mediated human-telerobot interaction
Sheik-Nainar, M. A., KABER, D. B., & Chow, M. (2005) · Human Factors and Ergonomics in Manufacturing & Service Industries · doi:10.1002/hfm.20025 · Cited by 31 · see citing works
Self-citationHuman-Robot Interface: Issues in Operator Performance, Interface Design, and Technologies
Chen, J. Y., Haas, E. C., Pillalamarri, K., & Jacobson, C. N. (2006) · doi:10.21236/ada451379 · Cited by 31 · see citing works
5G Enabled Technologies for Smart Education
Dake, D. K., & Adjei, B. (2019) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2019.0101228 · Cited by 30 · see citing works
Kim, E., Peysakhovich, V., & Roy, R. N. (2021) · ACM Symposium on Applied Perception · doi:10.1145/3474451.3476233 · Cited by 25 · see citing works
de Merwe, D. B. V., van Maanen, L., ter Haar, F. B., van Dijk, R. J. E., Hoeba, N., & der Stap, N. V. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-21565-1_11 · Cited by 22 · see citing works
Controlling robots in the home: Factors that affect the performance of novice robot operators
McGinn, C., Sena, A., & Kelly, K. (2017) · Applied Ergonomics · doi:10.1016/j.apergo.2017.05.005 · Cited by 20 · see citing works
Chen, J. Y. C., & Barnes, M. J. (2021) · Wiley eBooks · doi:10.1002/9781119636113.ch44 · Cited by 19 · see citing works
Development of the human interactive autonomy for the shared teleoperation of mobile robots
Lee, K., Mehmood, U., & Ryu, J.-H. (2016) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2016.7759247 · Cited by 16 · see citing works
Bidwell, J., Holloway, A., & Davidoff, S. (2014) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2556288.2557174 · Cited by 16 · see citing works
Pruks, V., Lee, K.-H., & Ryu, J.-H. (2018) · International Conference on Ubiquitous Robots (UR) · doi:10.1109/urai.2018.8441814 · Cited by 13 · see citing works
Evaluation of Human Factors for Assessing Human-Robot Interaction in Delayed Teleoperation
Wojtusch, J., Taubert, D., Graber, T., & Nergaard, K. (2018) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc.2018.00641 · Cited by 12 · see citing works
Emmerich, C., Nordmann, A., Swadzba, A., Steil, J. J., & Wrede, S. (2013) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2013.6631189 · Cited by 12 · see citing works
Ferketic, J., Goldblatt, L., Hodgson, E. W., Murray, S. N., Wichowski, R., Bradley, A., Fong, T., Chun, W. H., Stiles, R., Evans, J., et al. (2006) · SAE technical papers on CD-ROM/SAE technical paper series · doi:10.4271/2006-01-2019 · Cited by 12 · see citing works
Transparent interaction and human–robot collaboration for military operations
Lakhmani, S. G., Wright, J. L., & Chen, J. Y. C. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-815367-3.00001-3 · Cited by 9 · see citing works
Steil, J. J., Emmerich, C., Swadzba, A., Grünberg, R., Nordmann, A., & Wrede, S. (2013) · Springer tracts in advanced robotics · doi:10.1007/978-3-319-02934-4_6 · Cited by 8 · see citing works
Lee, K.-H., Pruks, V., & Ryu, J.-H. (2017) · International Conference on Ubiquitous Robots and Ambient Intelligence · doi:10.1109/urai.2017.7992775 · Cited by 8 · see citing works
The Utility of Measures of Attention and Situation Awareness for Quantifying Telepresence
Riley, J. M. (2001) · Cited by 8 · see citing works
Self-citationA User Interface for Telecontrol of a Robot Over the Internet
Behnke, R., & Elzer, P. F. (2001) · IFAC Proceedings Volumes · doi:10.1016/s1474-6670(17)41724-1 · Cited by 7 · see citing works
A Methodology to Assess the Human Factors Associated with Lunar Teleoperated Assembly Tasks
Kumar, A., Bell, M. M., Mellinkoff, B., Sandoval, A., Martin, W. B., & Burns, J. O. (2020) · IEEE Aerospace Conference (AERO) · doi:10.1109/aero47225.2020.9172667 · Cited by 6 · see citing works
Implementation of 5G Technology in Rural Education of India
Agrawal, U., Dave, P., Tiwari, A., Upadhyay, V., Sankhe, M. S., & Shrivastav, S. (2022) · IEEE Bombay Section Signature Conference (IBSSC) · doi:10.1109/ibssc56953.2022.10037466 · Cited by 6 · see citing works
Enabling Access to K-12 Education with Mobile Remote Presence
Cha, E., Sajid, Q., & Matarić, M. J. (2016) · National Conference on Artificial Intelligence · Cited by 6 · see citing works
Performance and Workload of Operators in a Human - Telerebot System
Žunjić, A. (2015) · International Journal of Behavioral Research & Psychology · doi:10.19070/2332-3000-150004e · Cited by 5 · see citing works
Laukka, E., Evan G. Center, Sakçak, B., LaValle, S. M., Ojala, T., & Pouke, M. (2024) · IEEE Conference on Telepresence · doi:10.1109/telepresence63209.2024.10841552 · Cited by 3 · see citing works
Learning Robotic Rotational Manipulation Skill from Bilateral Teleoperation
Lee, J. H., & Ryu, J.-H. (2022) · International Conference on Ubiquitous Robots (UR) · doi:10.1109/ur55393.2022.9826276 · Cited by 3 · see citing works
Evaluation of Subjective and Objective Performance Metrics for Haptically Controlled Robotic Systems
Pham, C. D., Phan, H. N. T., & From, P. J. (2014) · Modeling Identification and Control A Norwegian Research Bulletin · doi:10.4173/mic.2014.3.2 · Cited by 3 · see citing works
Telepresence and Performance in an Immersive Virtual Environment and Sporting Task
Ma, R. (2003) · NCSU Libraries Repository (North Carolina State University Libraries) · Cited by 3 · see citing works
Development of a Remote Steel Pipe Cutting Robot System
Shin, H., Bae, Y.-G., Jung, S., Choi, Y.-R., & Kim, C.-H. (2018) · International Conference on Ubiquitous Robots (UR) · doi:10.1109/urai.2018.8441772 · Cited by 3 · see citing works
A Comparison of Displays and Associated Workload on Nuclear Power Plants Tasks
Reinerman-Jones, L., Hughes, N., & D’Agostino, A. (2016) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1541931213601388 · Cited by 2 · see citing works
Haptic Field and Force Feedback Generation for Wheeled Vehicle Teleoperation on 2.5D Environments
Kim, Y., Kim, D., & Ryu, J.-H. (2024) · Lecture notes in networks and systems · doi:10.1007/978-3-031-44851-5_7 · Cited by 2 · see citing works
Image display visualization in teleoperation
Smith, J. M. J., DeJong, B. P., Karadoğan, E., & Hasbany, J. (2017) · IEEE Sensors Applications Symposium (SAS) · doi:10.1109/sas.2017.7894096 · Cited by 2 · see citing works
Lee, K.-H., Singh, H., Hulin, T., & Ryu, J.-H. (2022) · International Conference on Control, Automation and Systems (ICCAS) · doi:10.23919/iccas55662.2022.10003886 · Cited by 2 · see citing works
The effect of composite vs. first person perspective view in real world telerobotic operations
Jun, H. Y. (2011) · doi:10.31274/etd-180810-574 · Cited by 2 · see citing works
The Effect of Object Selection and Operator Movement on Situation Awareness in Virtual Reality
Krukowski, D. (2019) · doi:10.22215/etd/2019-13473 · Cited by 2 · see citing works
Social Cybernetics of Team Performance Variability
Smith, T. J., Henning, R. A., Wade, M. G., & Fisher, T. (2014) · CRC Press eBooks · doi:10.1201/b17319-12 · Cited by 1 · see citing works
Human Performance Operating Picture for Shepherding a Swarm of Autonomous Vehicles
Rojas, R. F., Debie, E., Fidock, J. J. T., Barlow, M., Kasmarik, K., Anavatti, S. G., Garratt, M., & Abbass, H. A. (2020) · Unmanned system technologies · doi:10.1007/978-3-030-60898-9_13 · Cited by 1 · see citing works
Currie, N. J., & Rochlis, J. (2004) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/154193120404800115 · Cited by 1 · see citing works
Perception is nothing without control (of velocity)
Bastianelli, A., Vicentini, M., Scandola, M., & Fiorini, P. (2012) · IRIS Research product catalog (Sapienza University of Rome)
Human Performance Variability: An Evolutionary Perspective
Smith, T. J., Henning, R. A., Wade, M. G., & Fisher, T. (2014) · CRC Press eBooks · doi:10.1201/b17319-15
Research on Human-robot Shared Control of Throat Swab Sampling Robot Based on Intention Estimation
Chen, Y., Song, F.-J., Yan, H.-F., Zhao, P., & Gong, Y. (2024) · International Journal of Control Automation and Systems · doi:10.1007/s12555-022-0728-x
Pham, T. A., & Espinosa-Leal, L. (2024) · Lecture notes in networks and systems · doi:10.1007/978-3-031-61905-2_40
Xiao, Y., Chen, S., & Li, Z. M. (2026) · Ergonomics · doi:10.1080/00140139.2026.2686857
GUDIPATI, S. K., & ANKAM, G. (2026) · Communications in computer and information science · doi:10.1007/978-3-032-30826-9_3
López-Contreras, E., Delaunoit, L., Coulon, A., Boyer, L., Paillet, A., Roy, R. N., Cowley, A., & Peysakhovich, V. (2026) · Frontiers in Space Technologies · doi:10.3389/frspt.2026.1920649
- Authors
- Kaber, D. B., Riley, J. M., Zhou, R., & Draper, J.
- Affiliations
- Mississippi State University (US)
- Oak Ridge National Laboratory (US)
- Venue
- Proceedings of the Human Factors and Ergonomics Society Annual Meeting
- Publisher
- SAGE Publications
- Published
- 2000-07
- Volume
- 44
- Issue
- 5
- Pages
- 503-506
- ISSN
- 0163-5182 (ISSN-L)
- 1071-1813
- 2169-5067
- OpenAlex
- W2065430148
- Cited by
- 63
- References
- 5
- Citations by year
- 2026: 3 · 2024: 4 · 2022: 3 · 2021: 4 · 2020: 3 · 2019: 6 · 2018: 4 · 2017: 5 · 2016: 3 · 2015: 1 · 2014: 5 · 2013: 2 · 2012: 3
- FWCI
- 4.96
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Proceedings of the Human Factors and Ergonomics Society Annual Meeting (publishedVersion)
- Topics
- Physical Sciences › Engineering › Mechanical Engineering › Teleoperation and Haptic Systems
- Physical Sciences › Computer Science › Human-Computer Interaction › Virtual Reality Applications and Impacts
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Keywords
- telepresence, teleoperation, telerobotics, virtual reality interface, control latency, control modes, video feedback, workload, pick-and-place task, human-machine interface design
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
