DESERTS: DElay-tolerant SEmi-autonomous Robot Teleoperation for Surgery

Gonzalez, Glebys; Agarwal, Mridul; Balakuntala, Mythra V.; Rahman, Mohd Azizi Abdul; Kaur, Upinder; Voyles, Richard M.; Aggarwal, Vaneet; Xue, Yexiang; Wachs, Juan P.

doi:10.1109/icra48506.2021.9561399

Cited by 14 publications

(4 citation statements)

References 33 publications

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“…Other similar examples include Refs. [21,22,[48][49][50][51][52][53][54][55][56][57][58][59][60][61].…”

Section: Modelling Network Delaymentioning

confidence: 99%

“…These approaches have been shown to give good results in terms of performance. The advanced methods for predictive display include the use of generative AI methods for pixel synthesis (e.g., GANs) [ 46 , 129 , 130 ], pixel transformation and time-series methods (e.g., LSTMs) [ 61 ], and probabilistic models [ 8 ]. Alternate methods that reduce the burden on computation and the interface can be considered, such as motion and content separation and extracting higher-level features in the visual feedback.…”

Section: Latency Mitigation Strategiesmentioning

confidence: 99%

See 1 more Smart Citation

Network Latency in Teleoperation of Connected and Autonomous Vehicles: A Review of Trends, Challenges, and Mitigation Strategies

Kamtam,

Lu,

Bouali

et al. 2024

Sensors

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With remarkable advancements in the development of connected and autonomous vehicles (CAVs), the integration of teleoperation has become crucial for improving safety and operational efficiency. However, teleoperation faces substantial challenges, with network latency being a critical factor influencing its performance. This survey paper explores the impact of network latency along with state-of-the-art mitigation/compensation approaches. It examines cascading effects on teleoperation communication links (i.e., uplink and downlink) and how delays in data transmission affect the real-time perception and decision-making of operators. By elucidating the challenges and available mitigation strategies, the paper offers valuable insights for researchers, engineers, and practitioners working towards the seamless integration of teleoperation in the evolving landscape of CAVs.

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“…Other similar examples include Refs. [21,22,[48][49][50][51][52][53][54][55][56][57][58][59][60][61].…”

Section: Modelling Network Delaymentioning

confidence: 99%

Section: Latency Mitigation Strategiesmentioning

confidence: 99%

Network Latency in Teleoperation of Connected and Autonomous Vehicles: A Review of Trends, Challenges, and Mitigation Strategies

Kamtam,

Lu,

Bouali

et al. 2024

Sensors

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show abstract

“…In tele-operations such as plant decommissioning, astrospace exploration and remote surgery [1], the exchange between position instructions from the master side and the haptic feedback from the slave side allows an operator to realistically conduct complicated tasks through a slave robot in a remote environment [2].…”

Section: Introductionmentioning

confidence: 99%

A Novel EMG-Based Variable Impedance Control Method for a Tele-Operation System Under an Unstructured Environment

Li²,

Chen

et al. 2022

IEEE Access

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In this paper, a novel variable impedance control method is proposed in bilateral tele-operation systems. Inspired by adaptability and stability of the human arm in unstructured environments, the varied parameters of the impedance state for the operator's arm are transferred to the slave robot to inherit the compliance profile of the human arm in this paper. Firstly, the impedance state of the arm is classified with the naï ve Bayes classifier, based on the surface electromyogram signals measured by the MYO arm band. Secondly, during teleoperation tasks, the operator can intuitively regulate the impedance of the arm based on attributes of the remote environment with the help of a haptic device, and a variable impedance control scheme is employed. The target impedance parameters of the impedance controller can change in real time according to the received impedance information of the operator's arm, so as to realize the simulation of the compliance profile of the slave robot to the human arm, and make the system maintain different compliance in different environments. The comparative experiments, with fixed impedance parameters and variable impedance parameters, are carried out to verify the effectiveness and the feasibility of the proposed method. The experimental results show that the method proposed in this paper has higher flexibility and environmental adaptability than the fixed impedance teleoperation method.

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“…Existing studies can be categorized based on user intention recognition techniques, task performance metrics, and decision-making algorithms. User intention recognition is performed either by model based methods [3], [6], [11], data-driven methods [1], [2], [7]- [10] or combinations of both types of methods [4]. It is worth noting that user intention recognition accuracy varies between 20% and 95%, which was not considered in some references.…”

Section: Introductionmentioning

confidence: 99%

Wireless Control for Life‐Critical Actions

Kizilkaya¹,

Chang²,

Zhao³

et al. 2020

Engineering and Technology for Healthcare

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Teleoperation can be very difficult due to limited perception, high communication latency, and limited degrees of freedom (DoFs) at the operator side. Autonomous teleoperation is proposed to overcome this difficulty by predicting user intentions and performing some parts of the task autonomously to decrease the demand on the operator and increase the task completion rate. However, decision-making for mode-switching is generally assumed to be done by the operator, which brings an extra DoF to be controlled by the operator and introduces extra mental demand. On the other hand, the communication perspective is not investigated in the current literature, although communication imperfections and resource limitations are the main bottlenecks for teleoperation. In this study, we propose an intelligent modeswitching framework by jointly considering mode-switching and communication systems. User intention recognition is done at the operator side. Based on user intention recognition, a deep reinforcement learning (DRL) agent is trained and deployed at the operator side to seamlessly switch between autonomous and teleoperation modes. A real-world data set is collected from our teleoperation testbed to train both user intention recognition and DRL algorithms. Our results show that the proposed framework can achieve up to 50% communication load reduction with improved task completion probability.

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DESERTS: DElay-tolerant SEmi-autonomous Robot Teleoperation for Surgery

Cited by 14 publications

References 33 publications

Network Latency in Teleoperation of Connected and Autonomous Vehicles: A Review of Trends, Challenges, and Mitigation Strategies

Network Latency in Teleoperation of Connected and Autonomous Vehicles: A Review of Trends, Challenges, and Mitigation Strategies

A Novel EMG-Based Variable Impedance Control Method for a Tele-Operation System Under an Unstructured Environment

Wireless Control for Life‐Critical Actions

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