Control Of Teleoperation Systems Research Articles

Robust Adaptive-Sliding-Mode Control for Teleoperation Systems with Time-Varying Delays and Uncertainties

Robust Adaptive-Sliding-Mode Control for Teleoperation Systems with Time-Varying Delays and Uncertainties

Adaptive Impedance Control for Teleoperation with Event-Triggered Controller

Uncertainty in the master–slave model is one of the primary factors affecting the transparency of teleoperation systems, and congestion in the master–slave communication network also greatly influences the performance of the teleoperation system. This paper proposes a combined framework of adaptive and impedance control to address the uncertainty in the master–slave model and achieve smooth operation at the slave end. Building upon this linear model, an event-triggered mechanism is designed using Lyapunov functions, with dynamic online adjustment of the triggering threshold parameters. Following the completion of the aforementioned research, control objectives are established to validate the performance of the teleoperation control system proposed in this paper. Finally, simulation verification is conducted in the Matlab/Simulink environment.

Predefined-Time Sensorless Admittance Tracking Control for Teleoperation Systems With Error Constraint and Personalized Compliant Performance

Predefined-Time Sensorless Admittance Tracking Control for Teleoperation Systems With Error Constraint and Personalized Compliant Performance

A master-slave teleoperation system control model based on model predictive control with fast dynamic response

A master-slave teleoperation system control model based on model predictive control with fast dynamic response

Sensorless force estimation of teleoperation system based on multilayer depth Extreme Learning Machine

The force feedback technology has a crucial impact on the precise control of teleoperation system. Robots in fields such as minimally invasive surgery and nuclear waste cannot integrate force sensors to obtain force feedback due to their end size and harsh working environment. In order to obtain end-effector force feedback in sensorless situation, a sensorless force estimation model based on artificial neural network is defined in this paper. For improving the model prediction ability, a new Multi-layer Depth Extreme Learning Machine (MDELM) is proposed. Firstly, the network structure of the extreme learning machine is redesigned, and the smoothing function and Gauss-Laplacian function are constructed as the feature extraction layer and enhancement layer of the MDELM model. Then, to further improve the prediction performance of MDELM, an improved Sooty Tern Optimization Algorithm (STOA) is introduced to optimize the parameters of the model. The results show that the proposed force estimator outperforms the existing model with an MAE of less than 0.205, which is at least 18.65% lower than the existing model. In addition, when the acceleration of the remote operating system is a fixed constant or the information is not available，a sensorless force feedback system can be constructed by combining motor torque, joint position and joint velocity parameter. In general, this study provides an effective force estimation solution for teleoperation system without force sensor.

GestureMoRo: an algorithm for autonomous mobile robot teleoperation based on gesture recognition

Gestures are a common way people communicate. Gesture-based teleoperation control systems tend to be simple to operate and suitable for most people’s daily use. This paper employed a LeapMotion sensor to develop a mobile robot control system based on gesture recognition, which mainly established connections through a client/server structure. The principles of gesture recognition in the system were studied and the relevant self-investigated algorithms—GestureMoRo, for the association between gestures and mobile robots were designed. Moreover, in order to avoid the unstably fluctuated movement of the mobile robot caused by palm shaking, the Gaussian filter algorithm was used to smooth and denoise the collected gesture data, which effectively improved the robustness and stability of the mobile robot’s locomotion. Finally, the teleoperation control strategy of the gesture to the WATER2 mobile robot was realized, and the effectiveness and practicability of the designed system were verified through multiple experiments.

Practical Preassigned Fixed-Time Fuzzy Control for Teleoperation System Under Scheduled Shared-Control Framework

Practical Preassigned Fixed-Time Fuzzy Control for Teleoperation System Under Scheduled Shared-Control Framework

Prescribed Performance Control for Teleoperation System of Nonholonomic Constrained Mobile Manipulator Without Any Approximation Function

The teleoperation system of mobile manipulator has been widely applied for space exploration, medical assistance, and other fields. To improve operational efficiency, this paper presents a novel prescribed performance synchronization control scheme without applying any approximation functions for a class of teleoperation system of the mobile manipulator with time-varying delays and nonholonomic constraints. Compared with the general manipulator system, the mobile manipulator has a larger workspace and stronger operability. Yet, the heterogeneity of master-slave robots and the nonholonomic constraint of slave robot bring many difficulties to the control of the system. Firstly, a prescribed performance function (PPF) is designed to guarantee that the position synchronization errors are remained within the predetermined boundary and converge to a small preset area within a preset time. Then, the direct force feedback information is introduced into the controller to improve the transparency of the teleoperation. In addition, there are no approximation functions applied in the proposed controller, which can significantly reduce the complexity and computation of the system. Finally, simulation and experimental results are made to illustrate the availability of this method for practical application. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —The motivation of this paper is to develop an algorithm to improve the steady-state and transient-state performance of mobile manipulator teleoperation system without increasing the complexity of the controller. Compared with the existing works, in this paper, the control algorithm without any approximators is proposed and a time-varying prescribed performance function is introduced, which promotes the steady-state and transient-state performance of the system essentially. At the same time, the introduction of force feedback information improves the transparency of the teleoperation system. The feasibility and effectiveness of the algorithm are verified on UR5e-Husky experimental platform. In the future, we will strive to further improve the transparency of the mobile manipulator teleoperation system in order to achieve the immersive effect of operator.

Fixed-time personalized variable gain tracking control for teleoperation systems with time varying delays

In this paper, a fixed-time personalized variable gain control (FTPGC) scheme is developed for a class of teleoperation systems. Efforts in this paper seek to improve the tracking performance under different operation intentions for teleoperation systems in the presence of time varying delays and uncertainties. By virtue of nonsmooth analysis, a fixed-time unknown observer (FUO) is firstly devised for the teleoperation systems such that the matched/mismatched unknowns can be observed within a fixed time. Meanwhile, with the help of an auxiliary function, a novel nonsingular fixed-time control framework is subsequently constructed without using any piecewise continuous switching functions. Moreover, the FUO and a variable gain involving electromyographic are incorporated into the fixed-time control framework, and thereby resulting the FTPGC scheme to improve trajectory tracking performance in the presence of unknowns and different operation intentions. The fixed-time stability of the entire FTPGC scheme is derived by rigorously theoretical analysis. Finally, comprehensive experiments and comparisons are conducted to demonstrate the effectiveness and feasibility of the proposed scheme.

Sliding-mode control for teleoperation system with uncertain kinematics and dynamics: An observer-based approach

This study concentrates on the tracking control of teleoperation system subjected to robot uncertainties. The coupling of kinematic and dynamic uncertainties poses a challenge to construct the teleoperation controller. To overcome this difficulty, an observer-based approach is designed to ensure position tracking while compensating for the unfavorable effects arising from the uncertainties. First, two sliding-mode observers together with a novel power reaching law are constructed, upon which, the uncertainties will be estimated in finite time. Next, a controller is proposed to solve the finite-time convergence of the tracking errors. The settling time and the stability of the closed-loop system are derived by Lyapunov’s direct method. Simulation results are presented to testify the tracking performance of the suggested control.

Fixed-time adaptive neural network synchronization control for teleoperation system with position error constraints and time-varying delay

Fixed-time adaptive neural network synchronization control for teleoperation system with position error constraints and time-varying delay

Sensor Fusion-Based Teleoperation Control of Anthropomorphic Robotic Arm

Sensor fusion is a technique that combines information from multiple sensors in order to improve the accuracy and reliability of the data being collected. In the context of teleoperation control of an anthropomorphic robotic arm, sensor fusion technology can be used to enhance the precise control of anthropomorphic robotic arms by combining data from multiple sensors, such as cameras, data gloves, force sensors, etc. By fusing and processing this sensing information, it can enable real-time control of anthropomorphic robotic arms and dexterous hands, replicating the motion of human manipulators. In this paper, we present a sensor fusion-based teleoperation control system for the anthropomorphic robotic arm and dexterous hand, which utilizes a filter to fuse data from multiple sensors in real-time. As such, the real-time perceived human arms motion posture information is analyzed and processed, and wireless communication is used to intelligently and flexibly control the anthropomorphic robotic arm and dexterous hand. Finally, the user is able to manage the anthropomorphic operation function in a stable and reliable manner. We also discussed the implementation and experimental evaluation of the system, showing that it is able to achieve improved performance and stability compared to traditional teleoperation control methods.

Design and Evaluation of an Intuitive Haptic Teleoperation Control System for 6-DoF Industrial Manipulators

Industrial robots are capable of performing automated tasks repeatedly, reliably and accurately. However, in some scenarios, human-in-the-loop control is required. In this case, having an intuitive system for moving the robot within the working environment is crucial. Additionally, the operator should be aided by sensory feedback to obtain a user-friendly robot control system. Haptic feedback is one way of achieving such a system. This paper designs and assesses an intuitive teleoperation system for controlling an industrial 6-DoF robotic manipulator using a Geomagic Touch haptic interface. The system utilises both virtual environment-induced and physical sensor-induced haptic feedback to provide the user with both a higher amount of environmental awareness and additional safety while manoeuvering the robot within its working area. Different tests show that the system is capable of fully stopping the manipulator without colliding with the environment, and preventing it from entering singularity states with Cartesian end effector velocities of up to 0.25 m/s. Additionally, an operator is capable of executing low-tolerance end effector positioning tasks (∼0.5 mm) with high-frequency control of the robot (∼100 Hz). Fourteen inexperienced volunteers were asked to perform a typical object removal and writing task to gauge the intuitiveness of the system. It was found that when repeating the same test for a second time, the participants performed 22.2% faster on average. The results for the second attempt also became significantly more consistent between participants, as the inter quartile range dropped by 82.7% (from 52 s on the first attempt to 9 s on the second).

Multiapproximator-based adaptive fault-tolerant control for teleoperation systems with deferred asymmetric time-varying output constraints

Multiapproximator-based adaptive fault-tolerant control for teleoperation systems with deferred asymmetric time-varying output constraints

Position Measurement Based Slave Torque Feedback Control for Teleoperation Systems With Time-Varying Communication Delays

Bilateral teleoperation system is referred to as a promising technology to extend human actions and intelligence to manipulating objects remotely. For the tracking control of teleoperation systems, velocity measurements are necessary to provide feedback information. However, due to hardware technology and cost constraints, the velocity measurements are not always available. In addition, the time-varying communication delay makes it challenging to achieve tracking task. This paper provides a solution to the issue of real-time tracking for teleoperation systems, subjected to unavailable velocity signals and time-varying communication delays. In order to estimate the velocity information, immersion and invariance (I&I) technique is employed to develop an exponential stability velocity observer. For the proposed velocity observer, a linear relationship between position and observation state is constructed, through which the need of solving partial differential and certain integral equations can be avoided. Meanwhile, the mean value theorem is exploited to separate the observation error terms, and hence, all functions in our observer can be analytically expressed. With the estimated velocity information, a slave-torque feedback control law is presented. A novel Lyapunov-Krasovskii functional is constructed to establish asymptotic tracking conditions. In particular, the relationship between the controller design parameters and the allowable maximum delay values is provided. Finally, simulation and experimental results reveal that the proposed velocity observer and controller can guarantee that the observation errors and tracking error converge to zero.

Adaptive time‐varying formation control for teleoperation system: A finite‐time approach

SummaryIn this article, the finite‐time formation control scheme is put forward for teleoperation system with time delay. First, a group of finite‐time observers are established to address the teleoperation system with time‐varying delay issue and via linearly parameterize to deal with the uncertainty in the system. The theory of self‐stable domain (SSR) is then applied to provide sufficient circumstances for the observers error dynamics to converge in finite‐time. Then, in line with the estimation of time delay derivatives to reconstruct the regression matrix as well as the adaptive law, the observer based time‐varying formation control protocol is drawn up. On the basis of finite‐time state‐independent input‐to‐output practical stable (FTSIIOpS) theorem, sufficient conditions for teleoperation implement time‐varying formation are developed. Finally, simulation is being used to validate the efficiency of the proposed strategy.

An Adaptive Proportional Plus Damping Control for Teleoperation Systems with Asymmetric Time-Varying Communication Delays

Communication delay is an important factor affecting the stability and performance of telerobotic systems. In this paper, a new adaptive proportional damping controller is proposed to improve the stability and performance of the system in the presence of the cases such as asymmetric communication delay, unknown gravity torque, friction torque, and other disturbance torques. The proposed proportional damping control method combines the RBF neural network and adaptive control strategy to compensate for the unknown torque. The stability and robustness of the system are enhanced by adding error-damping items, operator force, and environmental force items. The Lyapunov–Krasovskii functional is employed to analyze and prove the exponential stability and signal boundedness of the closed-loop system. The simulation results verify the correctness of the proposed method, and the comparison with the results of other control methods shows the effectiveness of the designed control strategy.

Bilateral continuous terminal sliding mode control for teleoperation systems with high-order disturbances

Bilateral continuous terminal sliding mode control for teleoperation systems with high-order disturbances

Featured Cover

The cover image is based on the Research Article Hierarchical predefi ned-time control of teleoperation systems with state and communication constraints by Jing-Zhe Xu et al., https://doi.org/10.1002/rnc.5789.

Hierarchical predefined‐time control of teleoperation systems with state and communication constraints

AbstractThe performance of the teleoperation system under multiple negative impacts cannot be easily predefined and regulated in general. This article aims to achieve the predefined performance of the teleoperation system under the effects of human operations, external disturbances, parametric uncertainties and communication constraints (including communication delays and quantized‐data communication). The predefined performance includes the state constraints (i.e., the joint‐space positions of the teleoperation system can be constrained in the predefined region throughout the control process) and predefined‐time set stability (i.e., the synchronization errors can be forced to reach an arbitrarily small neighborhood of the origin in a predefined time). To this end, a hierarchical predefined‐time control algorithm is newly designed via employing the error transformation method based on a novel limit‐time regulator. By using the barrier Lyapunov function, sufficient conditions on the control parameters are formally derived for guaranteeing the aforementioned performance. Finally, we present several simulation experiments to illustrate the effectiveness and advantages of the proposed main results.