Stability Of Teleoperation System Research Articles

Reinforcement Learning-Aided Edge Intelligence Framework for Delay-Sensitive Industrial Applications.

With the advancement in next-generation communication technologies, the so-called Tactile Internet is getting more attention due to its smart applications, such as haptic-enabled teleoperation systems. The stringent requirements such as delay, jitter, and packet loss of these delay-sensitive and loss-intolerant applications make it more challenging to ensure the Quality of Service (QoS) and Quality of Experience (QoE). In this regard, different haptic codec and control schemes were proposed for QoS and QoE provisioning in the Tactile Internet. However, they maximize the QoE while degrading the system’s stability under varying delays and high packet rates. In this paper, we present a reinforcement learning-based Intelligent Tactile Edge (ITE) framework to ensure both transparency and stability of teleoperation systems with high packet rates and variable time delay communication networks. The proposed ITE first estimates the network challenges, including communication delay, jitter, and packet loss, and then utilizes a Q-learning algorithm to select the optimal haptic codec scheme to reduce network load. The proposed framework aims to explore the optimal relationship between QoS and QoE parameters and make the tradeoff between stability and transparency during teleoperations. The simulation result indicates that the proposed strategy chooses the optimal scheme under different network impairments corresponding to the congestion level in the communication network while improving the QoS and maximizing the QoE. The end-to-end performance of throughput (1.5 Mbps) and average RTT (70 ms) during haptic communication is achieved with a learning rate and discounted factor value of 0.5 and 0.8, respectively. The results indicate that the communication system can successfully achieve the QoS and QoE requirements by employing the proposed ITE framework.

Stabilization of Teleoperation Systems with Communication Delays: An IMC Approach

The presence of time delays in communication introduces a limitation to the stability of bilateral teleoperation systems. This paper considers internal model control (IMC) design of linear teleoperation system with time delays, and the stability of the closed-loop system is analyzed. It is shown that the stability is guaranteed delay-independently. The passivity assumption for external forces is removed for the proposed design of teleoperation systems. The behavior of the resulting teleoperation system is illustrated by simulations.

Adaptive wavenet controller design for teleoperation systems with variable time delays using singular perturbation method

The main goal of controller design in teleoperation systems is to achieve stability and optimal operation in presence of factors such as time delays, system disturbances and modeling errors. This paper proposes a new method of controller design based on wavenet with singular perturbation method for the bilateral teleoperation of robots through the internet. The wavenet controller could overcome the variable time delay in teleoperation system. This new method introduces a reduced-order structure for control and stability of teleoperation systems. By using singular perturbation method, teleoperation system is decomposed into two fast and slow subsystems. This method is a step towards reduced-order modeling. In this method, we use a feedback linearization method in master subsystem and a wavenet controller for slave subsystem. In wavenet controller, we used a learning method so that the system was Lyapunov stable. As the stability of the model is highly dependent on the learning of the system, we use Lyapunov stability in this method. It has been tried to reduce the tracking error between the master and the slave subsystems. In this structure the position of master-slave are compared together and controlling signal is applied to the slave so that they can track each other in the least possible time. In all schemes the effectiveness of the system is shown through the simulations and they have been compared with each other.

Human dynamics and stability of teleoperator systems with generalized projection-based force reflection algorithms

AbstractA new general stability result for networked bilateral teleoperator systems with projection-based force reflection is presented. Contrary to the previous results, the human operator dynamics are taken into account in the stability analysis. The human dynamics are assumed to satisfy a general condition formulated in terms of finite distance between output of the human dynamics and a certain “passivity-based” stabilizing set. In particular, this assumption allows for both passive and non-passive behaviour of the human operator. The overall stability of the bilateral teleoperator system is proven in the presence of network-induced communication constraints for an arbitrary projection-based force reflection algorithm from a broad class.

Effect of Scaling on the Performance and Stability of Teleoperation Systems Interacting with Soft Environments

There is generally a tradeoff between stability and performance in haptic control systems. Teleoperation systems with haptic feedback are no exception. Scaling in these systems used in applications such as telemicrosurgical systems has further effects on the stability and performance. This paper focuses on those applications interacting with soft tissues and analyzes the effects of the scaling in an effort to increase the performance of these systems while maintaining the stability. Position tracking and kinesthetic perception are especially important in the tele-surgical systems and, hence, are used as the performance criteria. Quantitatively defined stability robustness, which is based on Llewellyn's absolute stability criterion, is used as a metric for stability analysis. Various choices of scaling factors, and human and environment impedances are then investigated. The proposed kinesthetic perception concept is validated using psychophysical experiments. Widely used bilateral control architectures such as the two-channel position–position, two-channel force–position and four-channel controls are specifically analyzed and evaluated using simulations and experiments with phantom soft tissues. Results also show that the force–position control architecture shows the best position tracking performance irrespective of the scaling factors while the four-channel controller shows the best kinesthetic perception capability.