Slave Manipulator Research Articles

A speed coordination control method based on D-S evidence synthesis theory

An adaptive speed coordination control method based on Dempster–Shafer (D-S) evidence synthesis theory is proposed to achieve the speed coordination of the slave manipulator under the condition of a large transmission delay in space teleoperation. First, the D-S evidence synthesis theory is applied to transform the speed coordination rule method. The model for predicting the manipulator’s future state is given to gain confidence in each state. Subsequently, performance comparison experiments of D-S evidence synthesis control theory, cascade control, fuzzy control, and adaptive fuzzy control are completed on the 3-degree-of-freedom (3-DOF) manipulator simulation platform. Finally, according to the experimental results, the accuracy of D-S evidence synthesis theory is 7.49% better than cascade control, 16.84% better than fuzzy control, and 28.45% better than adaptive fuzzy control. The adaptability of D-S evidence synthesis theory is generally superior to cascade control, slightly inferior to fuzzy control and inferior to adaptive fuzzy control.

The Adaptive Bilateral Control of Underwater Manipulator Teleoperation System with Uncertain Parameters and External Disturbance

A novel self-adaptive bilateral control strategy is introduced to manage uncertainties inherent in the teleoperation of an underwater manipulator system effectively. In response to uncertainties stemming from both the mathematical model and external disturbances, our approach offers innovative solutions. Firstly, to address uncertainties in the master model parameters, we propose a reference adaptive impedance control based on a nominal model. This control strategy dynamically adjusts the reference position of the desired model, leveraging adaptive control laws to compensate for model uncertainties. Additionally, to tackle uncertainties specific to the slave manipulator, we employ adaptive compensation using radial basis function (RBF) networks. Our unique combination of sliding mode variable structure controllers and robust adaptive controllers aims to mitigate approximation errors, ensuring precise tracking of the master manipulator’s position by the slave manipulator. By employing Lyapunov function analysis, we demonstrate the system’s superior tracking performance and global stability, with assured asymptotic convergence for force–position tracking. Through comprehensive experimentation, our results showcase the exceptional force–position tracking capabilities of the overall control system, even under challenging conditions of model uncertainties and external disturbances. Moreover, our system exhibits remarkable stability, reliability, and robustness, underscoring the effectiveness of our proposed adaptive control approach.

The nonlinear model reference adaptive impedance control for underwater manipulator operation objects in bilateral teleoperation system

The bilateral teleoperation system is susceptible to model parameter uncertainty and unknown disturbances in both the master and slave manipulators, resulting in instability and inaccuracies in the force and position tracking performance. To address these issues, a novel nonlinear model reference adaptive impedance controller has been designed to achieve coordinated force and position synchronization of dual manipulators. The adaptive control laws, based on sliding mode functions, have been designed to compensate for the uncertainty of the manipulator model. Furthermore, an adaptive estimation law has been employed to appraise the unknown upper bound of external disturbances. This ensures that the closed-loop model parameters of the dual manipulator converge to the reference impedance model respectively. Simultaneously, it enables the position error between the reference model response and the end-effector task space position to asymptotically converge to zero. To verify the effectiveness of the proposed controller, simulations have been conducted on the MATLAB platform and experiments on a single degree of freedom teleoperation system have been performed. The results demonstrate that the controller exhibits strong robustness and has the capability of force-position tracking ability.

Mixed-Reality-Based Teleoperation Grasping Control

Abstract Traditionally, teleoperation means that the system sends a series of signal commands from the master while the slave manipulator receives and realizes the desired control operations. For the purpose of implementing more dexterous and complex tasks, we propose a novel framework with dual-hand master teleoperation systems under time-varied delays. In this paper, we emphasize studying the bilateral grasping teleoperation control, as the time delay causes a communication outage. Combining a wave-variable structure with a four-channel framework, an event-trigger-based bilateral sliding mode teleoperation control and an adaptive neural network are designed to effectively achieve master-slave trajectory tracking. In the virtual 3D environment, we created a mixed-reality interface based on dual-hand master teleoperation control that effectively responded to the two Omni manipulators' position transformation of the virtual manipulator. The time delay between the real slave force feedback and the virtual interface is addressed by designed event-trigger-based control in order to efficiently reduce the impact of time communication outage. The system's stability is analyzed and robot experiments are performed. From the experimental results, the telepresence platform innovatively applied virtual force feedback to reveal the soft target grasping and to accurately estimate the interactive force, enabling sensorless force feedback control.

Master-slave Control Strategy of Surgical Robots for Gastrointestinal Surgery

The precise construction of the master-slave control strategy is a fundamental requirement for robot-assisted surgery. In this study, we propose a master-slave control strategy for gastrointestinal surgical robots based on the natural orifice transluminal endoscopic surgery surgical robot developed by Tianjin University. The forward and inverse kinematics of the continuum mechanism at the slave manipulator are investigated. A master-slave coordinate mapping system for surgical robots is established by analyzing the kinematic characteristics of the master and slave manipulators. Additionally, an intuitive mapping algorithm and a control flowchart for the robot are developed. The proportional control and incremental control strategies tailored for natural orifice transluminal endoscopic surgery procedures are proposed based on intuitive mapping control. Finally, a master-slave trajectory tracking experiment is performed to validate the feasibility of the proposed master-slave control strategy.

Force-reflecting event-triggered predefined-time cooperative control for teleoperation of NMMs via data-driven based observer

This paper investigates the cooperative control problem for the teleoperation system of networked mobile manipulators (NMMs), in which each mobile manipulator is subject to nonholonomic constraints, model uncertainty and external disturbances. The control objective of such a teleoperation system is to synchronize the task-space position between the human-controlled master manipulator and the slave mobile manipulators, and meanwhile enable the slave mobile manipulators to achieve a formation. For this purpose, a hierarchical predefined-time cooperative control (HPTCC) framework involving predefined-time distributed event-triggered (PTDET) estimator, predefined-time stability (PTS) controller and data-driven based (DDB) observer, is proposed. The PTDET estimator is used to generate the information that the slave mobile manipulators need to track and enable multiple slave mobile manipulators to interact through an event-triggered communication network. The PTS controller is presented to ensure the predefined-time stability of the master manipulator and the slave ones. Moreover, for improving the telepresence of the considered teleoperation system, the DDB observer is proposed to reestablish the interaction force between the slave mobile manipulators and the complex operating environment (i.e., the environmental force) on the human operator side. Based on the hierarchical control analysis as well as Lyapunov theory, several sufficient conditions are derived to guarantee the predefined-time stability for the teleoperation system of NMMs. Finally, several simulations are conducted to demonstrate the effectiveness of the proposed control scheme.

Distributed Neural-Network-Based Cooperation Control for Teleoperation of Multiple Mobile Manipulators Under Round-Robin Protocol.

This article addresses the distributed cooperative control design for a class of sampled-data teleoperation systems with multiple slave mobile manipulators grasping an object in the presence of communication bandwidth limitation and time delays. Discrete-time information transmission with time-varying delays is assumed, and the Round-Robin (RR) scheduling protocol is used to regulate the data transmission from the multiple slaves to the master. The control task is to guarantee the task-space position synchronization between the master and the grasped object with the mobile bases in a fixed formation. A fully distributed control strategy including neural-network-based task-space synchronization controllers and neural-network-based null-space formation controllers is proposed, where the radial basis function (RBF) neural networks with adaptive estimation of approximation errors are used to compensate the dynamical uncertainties. The stability and the synchronization/formation features of the single-master-multiple-slaves (SMMS) teleoperation system are analyzed, and the relationship among the control parameters, the upper bound of the time delays, and the maximum allowable sampling interval is established. Experiments are implemented to validate the effectiveness of the proposed control algorithm.

On the finite time force estimation for bilateral teleoperation of robot manipulators with time varying delays

One of the biggest challenges in the bilateral teleoperation of robot manipulators is to get transparency and telepresence between the local (master) and the remote (slave) manipulator. For these goals, it is advisable to transfer contact force measurements from one side to the other through the communication channel. However, there may be some reasons for which it is not necessarily desirable to employ force sensors. For instance, they are expensive, sensitive to noise, and they can be too big to be used in some small devices. Therefore, some estimation approaches may be advisable. This contribution shows the design of a position/force control scheme for bilateral teleoperators with time varying delays based on the estimation of velocities and forces by using only joint position measurements. Under some relaxed assumptions it is shown that position and force tracking errors become ultimately bounded with arbitrarily small ultimate bound in finite time. To the best of the authors’ knowledge there are no control schemes for bilateral systems with all the previous characteristics since the available ones assume constant time delays. The new proposal is tested by means of simulations and experiments showing a good performance both in free and constrained motion.

A Path Planning Method with a Bidirectional Potential Field Probabilistic Step Size RRT for a Dual Manipulator

The search efficiency of a rapidly exploring random tree (RRT) can be improved by introducing a high-probability goal bias strategy. In the case of multiple complex obstacles, the high-probability goal bias strategy with a fixed step size will fall into a local optimum, which reduces search efficiency. Herein, a bidirectional potential field probabilistic step size rapidly exploring random tree (BPFPS-RRT) was proposed for the path planning of a dual manipulator by introducing a search strategy of a step size with a target angle and random value. The artificial potential field method was introduced, combining the search features with the bidirectional goal bias and the concept of greedy path optimization. According to simulations, taking the main manipulator as an example, compared with goal bias RRT, variable step size RRT, and goal bias bidirectional RRT, the proposed algorithm reduces the search time by 23.53%, 15.45%, and 43.78% and decreases the path length by 19.35%, 18.83%, and 21.38%, respectively. Moreover, taking the slave manipulator as another example, the proposed algorithm reduces the search time by 6.71%, 1.49%, and 46.88% and decreases the path length by 19.88%, 19.39%, and 20.83%, respectively. The proposed algorithm can be adopted to effectively achieve path planning for the dual manipulator.

Hierarchical finite-time cooperative control for teleoperation of networked disturbed mobile manipulators

This paper investigates the teleoperation problem of networked disturbed mobile manipulators (NDMMs), in which the human operator remotely controls multiple slave mobile manipulators through a master manipulator. Each individual of the slave ones consisted of a nonholonomic mobile platform and a holonomic constrained manipulator that is mounted on the nonholonomic mobile platform. The cooperative control objective of the considered teleoperation problem includes: (1) synchronizing the states of the slave manipulators to the human-controlled master one; (2) forcing the mobile platforms of the slave ones to form a user-defined formation; (3) controlling the geometric center of all the platforms to track a reference trajectory. We present a hierarchical finite-time cooperative control (HFTCC) framework to achieve the cooperative control goal in a finite time. The presented framework includes the distributed estimator, the weight regulator and the adaptive local controller, where the estimator generates the estimated states of the desired formation and trajectory, the regulator selects the slave robot that the master one needs to track, as well as the presented adaptive local controller guarantees the finite-time convergence of the controlled states with model uncertainties and disturbances. Additionally, for improving the telepresence, a novel super twisting observer is presented to reconstruct the interaction force between the salve mobile manipulators and the remote operating environment on the master (i.e., the human) side. Finally, the effectiveness of the proposed control framework is demonstrated by several simulation results.

Bidirectional RRT*-Based Path Planning for Tight Coordination of Dual Redundant Manipulators

There are closed-chain constraints between the left manipulator and the right manipulator in tight coordination of the dual redundant manipulator. The existing planning algorithms suitable for loose coordination cannot be directly applied to tight coordination, as the planned path cannot satisfy the closed-chain constraints. To solve the above problem, a master-slave planning method based on bidirectional RRT* is proposed for dual redundant manipulators. Bidirectional RRT* is adopted to plan the path of the master manipulator. The path of the slave manipulator is calculated by terminal generalized velocity constraints instead of terminal position and posture constraints. Moreover, a local path replanning strategy is proposed to solve the problem that the planned path is actually not feasible due to the discontinuous joint path of the slave manipulator. The joint self-motion in the null space is utilized to keep the terminal position and posture of the slave manipulator unchanged. The proposed method is verified by simulations and experiments and the results show that it can solve the discontinuity problem, increase the success rate, shorten the planning time and satisfy closed-chain constraints. Therefore, the proposed method can be feasibly and effectively applied to the tight coordination of dual redundant manipulators.

Design and evaluation of vascular interventional robot system for complex coronary artery lesions.

At present, most vascular intervention robots cannot cope with the more common coronary complex lesions in the clinic. Moreover, the lack of effective force feedback increases the risk of surgery. In this paper, a vascular interventional robot that can collaboratively deliver multiple interventional instruments has been developed to assist doctors in the operation of complex lesions. Based on the doctor's skills and the delivery principle of interventional instruments, the main and slave manipulators of the robot system are designed. Haptic force feedback is generated through resistance measuring mechanism and active drag system. In addition, a force feedback control strategy based on force-velocity mapping is proposed to realize the continuous change of force and avoid vibration. The proposed robot system was evaluated through a series of experiments. The experimental results show that the system can accurately measure the delivery resistance of interventional instruments, and provide haptic force feedback to doctors. The capability of the system to collaboratively deliver multiple interventional instruments is effective. Therefore, it can be considered that the robot system is feasible and effective.

Gesture Recognition and Master–Slave Control of a Manipulator Based on sEMG and Convolutional Neural Network–Gated Recurrent Unit

AbstractSurface electromyography signal (sEMG) is the bio-electric signal accompanied by muscle contraction. For master–slave manipulation scenario such as patients with prosthetic hands, their upper limb sEMG signals can be collected and corresponded to the patient's gesture intention. Therefore, using a slave manipulator that integrated with the sEMG signal recognition module, the master side could control it to make gestures and meet their needs of daily life. In this paper, gesture recognition is carried out based on sEMG and deep learning, and the master–slave control of manipulator is realized. According to the results of training, the network model with the highest accuracy of gesture classification and recognition can be obtained. Then, combined with the integrated manipulator, the control signal of the manipulator corresponding to the gesture is sent to the control module of the manipulator. In the end, a prototype system is built and the master–slave control of the manipulator using the sEMG signal is realized.

6-DOF Bilateral Teleoperation Hybrid Control System for Power Distribution Live-Line Operation Robot

In the master-slave heterogeneous teleoperation, the workspace of the slave manipulator is usually much larger than that of the master manipulator. This paper proposes a 6-DOF bilateral hybrid teleoperation control strategy to map the workspace of the manipulators without changing the operation accuracy. The hybrid control includes the admittance and force control based on the feedback of the force sensor at the end of the manipulator. The two control strategies switched autonomously through the positioning of the Sigma.7 handle in the workspace. Compared with the classic bilateral teleoperation control, it overcomes the limitation of pre-matching the workspace of the master and slave. When the tool contacts a rigid environment, the robot can make adaptive compensation through the admittance controller even if the operator has not responded. We conduct extensive experiments to evaluate the changes in displacement and velocity before and after the switching process and under different admittance controller parameters. Finally, teleoperation is applied to live-line operation in distribution networks. The experiment proved that the control strategy is more consistent with human operation habits and can improve assembly success rate and efficiency.

Design and Evaluation of a Learning-Based Vascular Interventional Surgery Robot

Interventional therapy is one of the most effective methods for diagnosing and treating vascular-related diseases at present. It relies on achieving precise and safe navigation of intravascular tools within a patient’s vasculature. Vascular Interventional Surgical Robots (VISR) can reduce surgeons’ exposure to operational hazards including radiation. However, the absence of apt position control and force feedback remains a challenge. This study presents an isomorphic master–slave VISR for precise navigation of endovascular tools viz. catheters and guidewires. The master console aids operators in issuing manipulation commands and logs feedback from the force, rotation, and translation data. The slave manipulator uses the commands received from the master platform for actual tool navigation. However, precise master–slave position control and force feedback are precursors for optimal patient outcomes. This study utilized a fuzzy-PID controller for precise tool navigation and a neural network model for resistance force modulation with 50 mN precision. Furthermore, we evaluated the performance of using the learning-based models within our VISR and compared it with the performances from conventional methods. Results show that the models enhanced the proposed robotic system with better navigation precision, faster response speed, and improved force measurement capabilities.

Sliding Mode Impedance Control for Dual Hand Master Single Slave Teleoperation Systems

For the purpose of avoiding injury and realizing precise operations, the multilateral teleoperation system is the most efficient way to transport trace toxic or radioactive substances, to perform minimally invasive surgery, etc. It is essential to enhance the transparency of a multilateral teleoperation system including multiple masters and the single slave manipulator. However, there are few researchers focus on the allocation of the contact force of the single slave manipulator to different master manipulators. In this paper, we firstly introduce the concept of force translation for teleoperation systems consisting of dual hand master (left and right hands) manipulators and a single slave manipulator. Force translation reflects how the impedance on the single slave side is translated or allocated to contact forces on different master sides. To maintain the stability of the system and to improve transparency, we elucidate the mechanism of the force translation and analyze the relation among masters and the slave. Furthermore, the force translation mechanism is analyzed through numerical simulations and CHAI 3D virtual physical simulations. It is used to propose a multilateral impedance control, and the Lyapunov function is used to analyze the system stability. The results of numerical simulations and real robot experiments verify the effectiveness of the proposed control methods based on the proposed force translation mechanism.

Deep Learning-based Attack Detector for Bilateral Teleoperation Systems

A teleoperation system is referred to as a plant that is controlled remotely, and it is often composed of a human operator, a local master manipulator, and a remote slave manipulator, all connected by a communication network. Bilateral teleoperation systems (BTOS) include transmissions in both the forward and backward directions between the master and slave. This paper discusses a class of (BTOS) focusing on the security of the system after modeling the master and slave robots mathematically. The false data injection attack is examined, where the attacker may inject false data into the states that are being exchanged between the master and slave robots. The vulnerability of BTOS, where the attack destabilizes the system, is presented. A deep learning-based detection technique is proposed to detect the presence of false data injection attacks. The deep learning model with convolution neural network structure is trained and tested with considering complex attacks where the attacker has full knowledge of the system and proficiency to emanate and control the target system. The proposed model achieves 96\% validation accuracy, and the efficacy of the proposed deep learning detector is demonstrated and tested into the BTOS.

Control Strategy of Master-Slave Manipulator Based on Force Feedback for Decommissioning of Nuclear Facilities

To improve operation and reduce labor intensity during the process of decommissioning of nuclear facilities, a master-slave manipulation robot system based on force feedback for decommissioning of nuclear facilities is proposed, which is divided into three parts: master hand, wall-through pipe, and slave hand. The structure of master hand is designed according to the human-computer interaction design to add the perception of force information based on position perception. The master-slave manipulation system adopts a force-position hybrid control strategy; the position and force are sent to master and slave hand to discover telepresence operation. Incremental position control method realizes the workspace mapping between the master and the slave manipulator to improve the accuracy of the following performance. The novel zero-length spring compensation is designed to recognize the total gravity compensation of the force feedback device. Finally, the relative experiments have verified the work effectiveness of the master-slave manipulation system.

A Surgeon’s Habits-Based Novel Master Manipulator for the Vascular Interventional Surgical Master-Slave Robotic System

A master-slave vascular interventional surgical robotic system (MSVISRs) promises to treat cardio-cerebrovascular diseases without damaging the health of surgeons. Although many scholars are engaged in the research on the slave manipulator for the MSVISRs, there are very few studies on the master manipulator. In this study, a surgeon’s habits-based novel master manipulator is developed. This master manipulator imitates the operating habits of surgeons in surgery and uses a non-contact method with an optical mouse sensor to measure the operating displacements. The novelty of this approach is that this master manipulator with smaller size and non-contact displacement measurement method can provide the axial force and the circumferential force feedback independently. In this master manipulator, the rigid-flexible coupling structure is used to provide the axial force feedback. In addition, the brush DC motor is used to give the circumferential force feedback. Furthermore, the proposed master manipulator is calibrated and evaluated by experiments. The calibration experiments show that the maximum identification ranges for the axial force and circumferential force in the proposed master manipulator are 0.247-4.5N and 0.52-4.3N, respectively. Moreover, the evaluation experiments show that the maximum error is 0.8 mm in the axial direction. As compared with other master manipulator, the comprehensive properties of this novel master manipulator are shown to be better and more promising.

Kinetics Analysis and ADRC-Based Controller for a String-Driven Vascular Intervention Surgical Robotic System.

Vascular interventional surgery is a typical method for diagnosing and treating cardio-cerebrovascular diseases. However, a surgeon is exposed to significant X-radiation exposure when the operation is conducted for a long period of time. A vascular intervention surgical robotic system for assisting the surgeon is a promising approach to address the aforementioned issue. When developing the robotic system, a high displacement accuracy is crucial, and this can aid in enhancing operating efficiency and safety. In this study, a novel kinetics analysis and active disturbance rejection control (ADRC)-based controller is proposed to provide high accuracy for a string-driven robotic system. In this controller, kinetics analysis is initially used to improve the accuracy affected by the inner factors of the slave manipulator. Then, the ADRC controller is used to further improve the operating accuracy of the robotic system. Finally, the proposed controller is evaluated by conducting experiments on a vascular model. The results indicate maximum steady errors of 0.45 mm and 6.67°. The experimental results demonstrate that the proposed controller can satisfy the safety requirements of the string-driven robotic system.