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Luz, R., Silva, J. L. & Ventura, R. (2023). Enhanced teleoperation interfaces for multi-second latency conditions: System design and evaluation. IEEE Access. 11, 10935-10953
R. Luz et al., "Enhanced teleoperation interfaces for multi-second latency conditions: System design and evaluation", in IEEE Access, vol. 11, pp. 10935-10953, 2023
@article{luz2023_1734887492152, author = "Luz, R. and Silva, J. L. and Ventura, R.", title = "Enhanced teleoperation interfaces for multi-second latency conditions: System design and evaluation", journal = "IEEE Access", year = "2023", volume = "11", number = "", doi = "10.1109/ACCESS.2023.3240307", pages = "10935-10953", url = "https://ieeexplore.ieee.org/document/10026823" }
TY - JOUR TI - Enhanced teleoperation interfaces for multi-second latency conditions: System design and evaluation T2 - IEEE Access VL - 11 AU - Luz, R. AU - Silva, J. L. AU - Ventura, R. PY - 2023 SP - 10935-10953 SN - 2169-3536 DO - 10.1109/ACCESS.2023.3240307 UR - https://ieeexplore.ieee.org/document/10026823 AB - Adding human cognitive skills to planetary exploration through remote teleoperation can lead to more effective and valuable scientific data acquisition. Still, even small amounts of latency can significantly affect real-time operations, often leading to compromised robot safety, goal overshoot, and high levels of human mental fatigue and cognitive workload. Thus, novel operational strategies are necessary to cope with these effects. This paper proposes three augmented teleoperation interfaces that allow the user to operate a robot subject to 3 seconds of latency: (1) Avatar-Aided Interface (AAI), a semi-autonomous approach based on a virtual element; (2) Predictive Interface (PI), an approach with direct control and predictive elements; and (3) Hybrid Interface (HI), where the operator can easily switch between PI and AAI. We conducted a systematic within-subject experiment to evaluate the proposed interfaces in a realistic virtual environment with frequent traction losses. The user study compared AAI and PI to a Control Interface (CI), which did not display any augmented elements. The main results of this comparison showed that: (1) AAI led to a significant reduction in workload and a significant increase in usability and robot safety; (2) the use of the PI caused a significant increase in path length, indicating that operators overshoot their goals more often with this approach; (3) PI and AAI had lower reported effort; and (4) AAI is more flexible and effortless than PI and CI. Finally, the presented results show the need to consider uncertainty (e.g., traction loss) in future interface design. ER -