Title: Effects of Onset Latency and Robot Speed Delays on Mimicry-Control Teleoperation
In this paper, we study the effects of delays in a mimicry-control robot teleoperation interface which involves a user moving their arms to directly show the robot how to move and the robot follows in real time. Unlike prior work considering delays in other teleoperation systems, we consider delays due to robot slowness in addition to latency in the onset of movement commands. We present a human-subjects study that shows how different amounts and types of delays have different effects on task performance. We compare the movements under different delays to reveal the strategies that operators use to adapt to delay conditions and to explain performance differences. Our results show that users can quickly develop strategies to adapt to slowness delays but not onset latency delays. We discuss the implications of our results for the future development of methods designed to mitigate the effects of delays. more »« less
Tian, Nan; Tanwani, Ajay Kumar; Goldberg, Ken; Sojoudi, Somayeh
(, International Symposium on Robotics Research)
null
(Ed.)
Network latency is a major problem in Cloud Robotics for human robot interactions such as teleoperation. Routing delays can be highly variable in a heterogeneous computing environment, imposing challenges to reliably teleoperate a robot with a closed-loop feedback controller. By sharing Gaussian Mixture Models (GMMs), Hidden Semi- Markov Models (HSMMs), and linear quadratic tracking (LQT) con- trollers between the cloud and the robot. We build a motion recognition, segmentation, and synthesis framework for Cloud Robotic teleoperation; and we introduce a set of latency mitigation network protocols under this framework. We use this framework in experiments with a dynamic robot arm to perform learned hand-written letter motions.We then study the motion recognition errors, motion synthesis errors, and the latency mitigation performance.
Zhou, Tianyu; Ye, Yang; Zhu, Qi; Vann, William; Du, Jing
(, Frontiers in Human Neuroscience)
IntroductionAs robot teleoperation increasingly becomes integral in executing tasks in distant, hazardous, or inaccessible environments, operational delays remain a significant obstacle. These delays, inherent in signal transmission and processing, adversely affect operator performance, particularly in tasks requiring precision and timeliness. While current research has made strides in mitigating these delays through advanced control strategies and training methods, a crucial gap persists in understanding the neurofunctional impacts of these delays and the efficacy of countermeasures from a cognitive perspective. MethodsThis study addresses the gap by leveraging functional Near-Infrared Spectroscopy (fNIRS) to examine the neurofunctional implications of simulated haptic feedback on cognitive activity and motor coordination under delayed conditions. In a human-subject experiment (N= 41), sensory feedback was manipulated to observe its influences on various brain regions of interest (ROIs) during teleoperation tasks. The fNIRS data provided a detailed assessment of cerebral activity, particularly in ROIs implicated in time perception and the execution of precise movements. ResultsOur results reveal that the anchoring condition, which provided immediate simulated haptic feedback with a delayed visual cue, significantly optimized neural functions related to time perception and motor coordination. This condition also improved motor performance compared to the asynchronous condition, where visual and haptic feedback were misaligned. DiscussionThese findings provide empirical evidence about the neurofunctional basis of the enhanced motor performance with simulated synthetic force feedback in the presence of teleoperation delays. The study highlights the potential for immediate haptic feedback to mitigate the adverse effects of operational delays, thereby improving the efficacy of teleoperation in critical applications.
Du, Jing; Vann, William; Zhou, Tianyu; Ye, Yang; Zhu, Qi
(, Scientific Reports)
Abstract In the realm of robotics and automation, robot teleoperation, which facilitates human–machine interaction in distant or hazardous settings, has surged in significance. A persistent issue in this domain is the delays between command issuance and action execution, causing negative repercussions on operator situational awareness, performance, and cognitive load. These delays, particularly in long-distance operations, are difficult to mitigate even with the most advanced computing advancements. Current solutions mainly revolve around machine-based adjustments to combat these delays. However, a notable lacuna remains in harnessing human perceptions for an enhanced subjective teleoperation experience. This paper introduces a novel approach of sensory manipulation for induced human adaptation in delayed teleoperation. Drawing from motor learning and rehabilitation principles, it is posited that strategic sensory manipulation, via altered sensory stimuli, can mitigate the subjective feeling of these delays. The focus is not on introducing new skills or adapting to novel conditions; rather, it leverages prior motor coordination experience in the context of delays. The objective is to reduce the need for extensive training or sophisticated automation designs. A human-centered experiment involving 41 participants was conducted to examine the effects of modified haptic cues in teleoperations with delays. These cues were generated from high-fidelity physics engines using parameters from robot-end sensors or physics engine simulations. The results underscored several benefits, notably the considerable reduction in task time and enhanced user perceptions about visual delays. Real-time haptic feedback, or the anchoring method, emerged as a significant contributor to these benefits, showcasing reduced cognitive load, bolstered self-confidence, and minimized frustration. Beyond the prevalent methods of automation design and training, this research underscores induced human adaptation as a pivotal avenue in robot teleoperation. It seeks to enhance teleoperation efficacy through rapid human adaptation, offering insights beyond just optimizing robotic systems for delay compensations.
Perera, Dulanjana M.; Arachchige, Dimuthu D.; Mallikarachchi, Sanjaya; Ghafoor, Talal; Kanj, Iyad; Chen, Yue; Godage, Isuru S.
(, 2023 IEEE International Conference on Soft Robotics (RoboSoft))
Soft robotics holds tremendous potential for various applications, especially in unstructured environments such as search and rescue operations. However, the lack of autonomy and teleoperability, limited capabilities, absence of gait diversity and real-time control, and onboard sensors to sense the surroundings are some of the common issues with soft-limbed robots. To overcome these limitations, we propose a spatially symmetric, topologically-stable, soft-limbed tetrahedral robot that can perform multiple locomotion gaits. We introduce a kinematic model, derive locomotion trajectories for different gaits, and design a teleoperation mechanism to enable real-time human-robot collaboration. We use the kinematic model to map teleoperation inputs and ensure smooth transitions between gaits. Additionally, we leverage the passive compliance and natural stability of the robot for toppling and obstacle navigation. Through experimental tests, we demonstrate the robot's ability to tackle various locomotion challenges, adapt to different situations, and navigate obstructed environments via teleoperation.
Wang, Yeping; Sifferman, Carter; Gleicher, Michael
(, The 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023))
We explore task tolerances, i.e., allowable position or rotation inaccuracy, as an important resource to facilitate smooth and effective telemanipulation. Task tolerances provide a robot flexibility to generate smooth and feasible motions; however, in teleoperation, this flexibility may make the user’s control less direct. In this work, we implemented a telema- nipulation system that allows a robot to autonomously adjust its configuration within task tolerances. We conducted a user study comparing a telemanipulation paradigm that exploits task tolerances (functional mimicry) to a paradigm that requires the robot to exactly mimic its human operator (exact mimicry), and assess how the choice in paradigm shapes user experience and task performance. Our results show that autonomous adjustments within task tolerances can lead to performance improvements without sacrificing perceived control of the robot. Additionally, we find that users perceive the robot to be more under control, predictable, fluent, and trustworthy in functional mimicry than in exact mimicry.
Rakita, Daniel, Mutlu, Bilge, and Gleicher, Michael. Effects of Onset Latency and Robot Speed Delays on Mimicry-Control Teleoperation. Retrieved from https://par.nsf.gov/biblio/10172199. HRI '20: Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction . Web. doi:10.1145/3319502.3374838.
Rakita, Daniel, Mutlu, Bilge, & Gleicher, Michael. Effects of Onset Latency and Robot Speed Delays on Mimicry-Control Teleoperation. HRI '20: Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction, (). Retrieved from https://par.nsf.gov/biblio/10172199. https://doi.org/10.1145/3319502.3374838
Rakita, Daniel, Mutlu, Bilge, and Gleicher, Michael.
"Effects of Onset Latency and Robot Speed Delays on Mimicry-Control Teleoperation". HRI '20: Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction (). Country unknown/Code not available. https://doi.org/10.1145/3319502.3374838.https://par.nsf.gov/biblio/10172199.
@article{osti_10172199,
place = {Country unknown/Code not available},
title = {Effects of Onset Latency and Robot Speed Delays on Mimicry-Control Teleoperation},
url = {https://par.nsf.gov/biblio/10172199},
DOI = {10.1145/3319502.3374838},
abstractNote = {In this paper, we study the effects of delays in a mimicry-control robot teleoperation interface which involves a user moving their arms to directly show the robot how to move and the robot follows in real time. Unlike prior work considering delays in other teleoperation systems, we consider delays due to robot slowness in addition to latency in the onset of movement commands. We present a human-subjects study that shows how different amounts and types of delays have different effects on task performance. We compare the movements under different delays to reveal the strategies that operators use to adapt to delay conditions and to explain performance differences. Our results show that users can quickly develop strategies to adapt to slowness delays but not onset latency delays. We discuss the implications of our results for the future development of methods designed to mitigate the effects of delays.},
journal = {HRI '20: Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction},
author = {Rakita, Daniel and Mutlu, Bilge and Gleicher, Michael},
}
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