Slave Robot Research Articles

Application research of master-slave cranio-maxillofacial surgical robot based on force feedback

The complex anatomical structure, limited field of vision, and easily damaged nerves, blood vessels, and other anatomical structures are the main challenges of a cranio-maxillofacial (CMF) plastic surgical robot. Bearing these characteristics and challenges in mind, this paper presents the design of a master-slave surgical robot system with a force feedback function to improve the accuracy and safety of CMF surgery. A master-slave CMF surgical robot system based on force feedback is built with the master tactile robot and compact slave robot developed in the laboratory. Model-based master robot gravity compensation and force feedback mechanism is used for the surgical robot. Control strategies based on position increment control and ratio control are adopted. Aiming at the typical mandibular osteotomy in CMF surgery, a scheme suitable for robot-assisted mandibular osteotomy is proposed. The accuracy and force feedback function of the robot system under direct control and master-slave motion modes are verified by experiments. The drilling experiment of the mandible model in direct control mode shows that the average entrance point error is 1.37 ± 0.30 mm, the average exit point error is 1.30 ± 0.25 mm, and the average posture error is 2.27° ± 0.69°. The trajectory tracking and in vitro experiment in the master-slave motion mode show that the average position following error is 0.68 mm, and the maximum force following error is 0.586 N, achieving a good tracking and force feedback function. The experimental results show that the designed master-slave CMF robot can assist the surgeon in completing accurate mandibular osteotomy surgery. Through force feedback mechanism, it can improve the interaction between the surgeon and the robot, and complete tactile trajectory movements.

Neural network-based physiological organ motion prediction and robot impedance control for teleoperated beating-heart surgery

Compared to conventional arrested heart surgery, beating-heart surgery is promising as the advantages of eliminating adverse effects caused by a heart-lung bypass machine and enabling intraoperative evaluation of heart motion. However, the fast motion of the heart introduces a significant challenge for beating-heart surgery. In this paper, a teleoperation system, which employs an impedance control for the master robot and an ultrasound image-based position control for the slave robot (surgical robot), is proposed to achieve non-oscillatory force feedback and heart motion compensation, respectively. Specifically, an impedance model is designed for the master robot to provide the human operator (surgeon) with non-oscillatory haptic feedback. To compensate for the beating heart’s motion, ultrasound imaging is used to obtain the position of the point of interest (POI) on the heart tissue. As the use of ultrasound imaging introduces non-negligible time delay caused by image acquisition and processing, a recurrent neural network (NN)-based physiological organ motion predictor is proposed. The predicted POI position is used to control the slave robot to automatically compensate for the beating heart’s motion. The proposed method is validated through experiments. The proposed control strategy with NN-based heart motion predictor is compared to the other two strategies without heart motion predictor and with an extended Kalman filter (EKF)-based heart motion predictor. The experimental results present that the proposed strategy with NN algorithm shows significant advantages (higher synchronization accuracy and relatively steady slave-heart contact force) over the other two strategies.

Dual-Master/Single-Slave Haptic Teleoperation System for Semiautonomous Bilateral Control of Hexapod Robot Subject to Deformable Rough Terrain

The increasing application requirements of multilegged walking robots in outdoor environments pose new challenges regarding the design of their teleoperation systems. Some of these challenges arise from the multiple degrees of freedom of the telerobotic system and nonpassive exogenous disturbance. Herein, a novel control system based on a dual-master/single-slave bilateral haptic teleoperation framework using a semiautonomous strategy for hexapod robots walking on deformable rough terrains is proposed. In this teleoperation system, the body velocities and postures of the hexapod robot are determined according to the positions of two haptic master robots. The proposed teleoperator includes a time-domain passivity control approach to compensate for the system’s potential nonpassivity induced by the contact slippage between the foot and the ground. Furthermore, a posture-level bilateral controller is designed to overcome the unpredictable posture vibration. Information about the velocity loss and posture error is displayed to the human operator in the form of haptic force. In the underlying controller of the slave robot, a foot-force optimization algorithm is developed to improve the local autonomy of the teleoperation system. Furthermore, the stability of the system is demonstrated by its passivity. Experimental results indicate that the proposed controllers can provide a stable and transparent bilateral haptic teleoperation system for a hexapod robot under environmental perturbations.

Swarm Robotics: A New Framework of Military Robots

In Industries robots are programmed to perform specified tasks like and place, packaging, transporting etc. Every robots need to be programmed individually to accomplish the task given. In the proposed work one master robots is designed and programmed in such a way that can train number of slave robots sequentially to perform multiple tasks at different processing lines of an industry this reduces the complexity in programming individual robots for different operations and also without programming the slave robots. This Robot plays a vital role in Industry Automation. Servomotors are used to achieve rotational motion of the robotic arm and Lora module to train slave robots. A robot is a machine that can perform task operation. A robot is a machine can perform specific task automatically or the guidance. The project proposes robotic vehicle that has an intelligent built in its that it directs itself whenever an obstacle comes in its path. An ultrasonic sensor is used to detect any obstacle in front of it and sends a command to the ArduinoNano.

Stability Data Xbee S2b Zigbee Communication on Arduino Based Sumo Robot

Wireless technology is a solution to reach hard-to-reach places using cable technology. The use of wireless technology can reach these areas without using copper or cables in the data transmission process. Communication technology using wireless is one solution to connect the control system to support the creation and achievement of the goals of the 4.0 revolution so that control and monitoring become easier. With the convenience provided by wireless technology such as connecting various types of system devices between other systems. One type of wireless technology is WPAN, especially on the ZigBee system from Digi International with the IEEE 802.15.4 protocol standard with low power consumption and working at a frequency of 2.4 GHz. Utilization of the communication system from the ZigBee protocol can control according to the range capabilities of the ZigBee system. ZigBee's ability and use of communication can perform communication control robot sumobot (slave robot) and remote control (robot leader) as an introduction to command data to carry out movements on the slave robot in accordance with the orders from the robot leader After trying XBEE to send data at a certain distance without experiencing data loss, the best distance is obtained, namely 1 - 100 meters with the firmware coordinator and router settings. Data delays can be minimized with a transfer rate of 3 kbps in the data transfer rate.

Simpsons 1/3 base fuzzy neural network with passive controller of wheeled mobile robot system

The paper investigates Passivity of Simpson 1/3 rule fuzzy neural network controller by teleoperation-based wheeled mobile robot navigation and wheel slippage. To render the obstacle avoidance for wheeled mobile robot and ensuring incident-free navigation particularly unlimited workspace and surface slippage of coordination for master robot position and slave robot velocity, a passivity controller mode is employed. Effective control strategies are formulated to achieve system stability in which soft-computing methodology is accessed to bypass robot wheel slippage and skidding. Soft-computing based fuzzy neural network system is framed through Simpson 1/3 rule for reducing master/slave robot position error on behalf of unavoidable and acceptable forces, which is confirmed by teleoperation system. We concluded mathematically, the system stability which has been shown via its passivity of the fuzzy neural network controller. The forces which can be handled by the human operator are approximately equal to the forces applied by the environmental force and sensor predictor of slave robot whichever comes under the unlimited workspace. Simulation results are verified with the effect of the proposed controller. Index Terms: Autonomous wheeled mobile robot, Passivity, adaptive network fuzzy inference system, Simpson’s 1/3 rule, teleoperation system.

Remote Assessment of Post-Stroke Elbow Function Using Internet-Based Telerobotics: A Proof-of-Concept Study.

Purpose: Upper limb hemiparesis is the most common impairment in stroke survivors, and adequate assessment is crucial for setting the rehabilitation strategy and monitoring the effect of treatment. However, adequate timely assessments are difficult due to the limited accessibility to clinics for stroke survivors. We designed this study to investigate whether teleassessments for motor impairments of the spastic elbow (i.e., passive range of motion (PROM), muscle strength, and spasticity) are feasible in stroke survivors.Methods: To implement a telerobotic system for remote assessment with physical interaction, we constructed a system with a master robot interacting with a doctor (assessor) and a slave robot interacting with the elbow of a subject with stroke. The master robot is operated by the doctor, where the torque and the speed are transferred to the slave robot via the Internet, and the reaction of the patient's elbow to the slave robot's movement is measured with a torque sensor, then finally transferred back to the master robot. An intercontinental remote assessment, which is considered one of the worst possible scenarios, was used as a clinical test to strictly check the feasibility. For the clinical tests, the examiner for the teleassessment was located at a lab in the National Institutes of Health (NIH, Bethesda, MD, USA) while the stroke patients were located at Seoul National University Bundang Hospital (Bundang, Kyeonggido, South Korea).Results: In total, 12 stroke patients' elbows (age range, 28–74; M:F = 6:6) were tested. For the PROM, the absolute difference between two assessments (in-person vs. remote) was 5.98 ± 3.51° on average (range, 0–11.2). The agreements for the strength and the spasticity of elbow flexor between in-person and remote assessments were substantial (k = 0.643) and fair (k = 0.308), respectively. No adverse events were observed during or immediately after the telerobotic assessment.Conclusions: Internet-based telerobotic remote assessment for motor impairment of spastic elbow in stroke using our system is feasible even in the worst setting, with too long of a distance and a delayed communication network.

Passive Adaptive Network Fuzzy Inference Controller Basedwheeled Mobile Robot

Passive adaptive network fuzzy inference controllerby teleoperation based wheeled mobile robot navigationand wheel slippage has been envisaged in this paper. Apassivity controller mode is employed to render the obstacleavoidance for wheeled mobile robot thereby ensuring incidentfree navigation particularly unlimited workspace andsurface slippage of coordination of master robot positionand slave robot velocity. In order to achieve system stabilityeffective control strategies has been formulated. Thesestrategies bypass robot slippage and skidding due to softcomputing.Perfect position tracking of the master/ slaverobot with Simpson 1/3 rule based adaptive neural networkfuzzy inference system is reducing the error in terms ofunavoidable and acceptable forces, which is confirmed bypassivity. We demonstrated theoretically, the systems stabilityis shown via its passivity hybrid system in that force feltby the human operator is approximately equal to the forcesapplied by the environment force and sensor predictor ofslave robot, which is a satisfactory performance outcome.Simulation results verify the effectiveness of the proposedscheme for teleoperation under passivity controller.

A novel robotic system for flexible ureteroscopy.

Interventional robots currently exist for flexible ureteroscopy (fURS). However, force feedback and intra-renal pressure, which are important in fURS, were rarely considered when designing these robots. We propose a novel robotic system for fURS integrated with partial force feedback function that is the bending knob's torque feedback of the flexible ureteroscope, and intra-renal pressure monitoring. The proposed robotic system adopts commercial haptic device to realize torque feedback. In addition, we further propose a neural network-based method to optimize the operation of above haptic device. Experimental results show that the slave robot can capture the variation of bending conditions and feedback to the operator, and can also accurately monitor the intra-renal pressure. Besides, the neural network-based method shows its potential in improving the operation. The results confirm the feasibility of proposed robot's functions. In vivo experiments are needed to further evaluate this system in future work.

A passivity-based control strategy for nonlinear bilateral teleoperation employing estimated external forces

Teleoperation systems have been presented to handle objects in environments in which the presence of operators are impracticable, unsafe or less effective. In this paper, a passive control strategy employing the new outputs to state synchronization of the master and slave robots is developed to attain position coordination during contact tasks. The proposed control scheme includes position signals plus force signals. However, force measurement in such applications is a major limitation. Therefore, a modified force estimation algorithm is proposed to predict external forces applied on the master and slave robots. The closed-loop bilateral teleoperation system is investigated by employing Lyapunov stability criteria. Finally, the experimental results demonstrate the efficiency of the proposed control scheme. It is observed that, in the presence of the estimated external forces in the control scheme, the slave robot follows the master position in both free and contact motion, and force reflecting occurs properly as well. Moreover, it is verified that the external forces are estimated appropriately through the proposed force estimation algorithm.

Development of Robot-Assisted Untact Swab Sampling System for Upper Respiratory Disease

We propose a new telerobotic system for untact swab sampling to prevent the infection of medical staff during upper respiratory sample collection. The system consists of a slave robot and two master devices. The slave robot is designed to move a swab in 6 degrees of freedom within the facial area and to insert and remove the swab under remote control by an operator at the master site based on magnified imaging of the patient’s facial area. The insertion and removal of the swab into and from the nostril are implemented by means of a swab insertion unit; as the counterpart to this unit, the master system also includes a swab insertion device to control the swab insertion unit remotely. A force sensor installed on the swab holder enables monitoring of the force generated when the swab touches the target. In experiments, a virtual specimen was installed on the posterior nasopharynx wall of a life-size head phantom model. The nasopharyngeal swab samplings of the phantom model were successfully performed thanks to the force monitoring capability of the proposed telerobotic system, showing that this system is suitable for remote upper respiratory sample collection.

Failure-distribution-dependent H∞ fuzzy fault-tolerant control for multiple-degree-of-freedom nonlinear bilateral teleoperation system

In this paper, a novel failure-distribution-dependent H∞ fuzzy fault-tolerant control algorithm is proposed for a type of multiple-degree-of-freedom (MDOF) nonlinear bilateral teleoperation systems with partial actuator failures and time-varying communication delays. At first, the nonlinear systems are modeled as T-S fuzzy systems with multiple time-varying delays. The upper bound and lower bound of the transmission delays are incorporated in the stability analysis. When actuator failures exist in both master and slave robot, based on the characteristic of failures and delays, H∞ fuzzy fault-tolerant controllers are designed by using free-weight matrix approach. After this, a sufficient condition is provided to ensure the mean square stable of the closed-loop system with a disturbance attenuation level γ. Finally, numerical examples are provided to show the effectiveness of the proposed methods.

Adaptive Type-2 Fuzzy Neural-Network Control for Teleoperation Systems With Delay and Uncertainties

Interacting with human operators, remote environment, and communication networks, teleoperation systems are considerably suffering from complexities and uncertainties. Managing these is of paramount importance for safe and smooth performance of teleoperation systems. Among the countless solutions developed by researchers, type-2 fuzzy (T2F) algorithms have shown an outstanding performance in modeling complex systems and tackling uncertainties. Moreover, artificial neural networks (NNs) are well known for their adaptive learning potentials. This article proposes an adaptive interval type-2 fuzzy neural-network control scheme for teleoperation systems with time-varying delays and uncertainties. The T2F models are developed based on the experimental data collected from a teleoperation setup over a local computer network. However, the resulted controller is evaluated on an intercontinental communication network through the Internet between Australia and Scotland. Moreover, the slave robot and the remote workspace are completely different and unforeseen. Stability and performance of the proposed control is analyzed by Lyapunov–Krasovskii method. Comprehensive comparative studies demonstrate that the proposed controller outperforms traditional techniques in experimental evaluations.

Investigation of a Hybrid Kinematic Calibration Method for the “Sina” Surgical Robot

Calibrating the inverse kinematics of complex robots is often a challenging task. Finding analytical solutions is not always possible and the convergence of numerical methods is not guaranteed. The model-free approaches, based on machine learning and artificial intelligence, are fast and easy to work, however, they need a huge amount of experimental training data to provide acceptable results. In this article, we proposed a hybrid method to benefit the advantage of both model-based and model-free approaches. The forward kinematics of the robot is calibrated using a model-based approach, and its inverse kinematics using a neural network. Hence, while there is no need to solve the nonlinear inverse kinematic equations, the training data of the neural network is generated artificially by the calibrated forward kinematic model. The implementation of the proposed methodology on slave robot of the “Sina” surgical system revealed reasonably good results. The accuracy improved by ${\bf 53\%}$ and ${\bf 43\%}$ for position and orientation, respectively, after calibration.

Asymmetric Bilateral Telerobotic System With Shared Autonomy Control

The asymmetry in bilateral teleoperation, i.e., the differences of mechanical structures, sizes, and number of joints between the master and slave robots, can introduce kinematics redundancy and workspace inequality problems. In this article, a novel shared autonomy control strategy is proposed for handling the asymmetry of bilateral teleoperation, which has two main contributions. First, to deal with kinematics redundancy, the proposed strategy provides a self-regulation algorithm of orientation that allows the operator to solely use the master position command to simultaneously control the slave's position and orientation. Second, to deal with workspace inequality, the proposed strategy enables the slave's workspace to be dynamically tunable to adapt to various task spaces without influencing the smoothness of the robot's movement. The experiments on a platform consisting of a six-degree of freedom (DoF) UR10 robot and a 3-DoF haptic device are given to validate the effectiveness of the proposed control strategy.

Structural health monitoring of railway tracks using IoT-based multi-robot system

A multi-robot-based fault detection system for railway tracks is proposed to eliminate manual human visual inspection. A hardware prototype is designed to implement a master–slave robot mechanism capable of detecting rail surface defects, which include cracks, squats, corrugations, and rust. The system incorporates ultrasonic sensor inputs coupled with image processing using OpenCV and deep learning algorithms to classify the surface faults detected. The proposed Convolutional Neural Network (CNN) model fared better compared to the Artificial Neural Network (ANN), random forest, and Support Vector Machine (SVM) algorithms based on accuracy, R-squared value, F1 score, and Mean-Squared Error (MSE). To eliminate manual inspection, the location and status of the fault can be conveyed to a central location enabling immediate attention by utilizing GSM, GPS, and cloud storage-based technologies. The system is extended to a multi-robot framework designed to optimize energy utilization, increase the lifetime of individual robots, and improve the overall network throughput. Thus, the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol is simulated using 100 robot nodes, and the corresponding performance metrics are obtained.

Vision-based hand-eye calibration for robot-assisted minimally invasive surgery.

The knowledge of laparoscope vision can greatly improve the surgical operation room (OR) efficiency. For the vision-based computer-assisted surgery, the hand-eye calibration establishes the coordinate relationship between laparoscope and robot slave arm. While significant advances have been made for hand-eye calibration in recent years, efficient algorithm for minimally invasive surgical robot is still a major challenge. Removing the external calibration object in abdominal environment to estimate the hand-eye transformation is still a critical problem. We propose a novel hand-eye calibration algorithm to tackle the problem which relies purely on surgical instrument already in the operating scenario for robot-assisted minimally invasive surgery (RMIS). Our model is formed by the geometry information of the surgical instrument and the remote center-of-motion (RCM) constraint. We also enhance the algorithm with stereo laparoscope model. Promising validation of synthetic simulation and experimental surgical robot system have been conducted to evaluate the proposed method. We report results that the proposed method can exhibit the hand-eye calibration without calibration object. Vision-based hand-eye calibration is developed. We demonstrate the feasibility to perform hand-eye calibration by taking advantage of the components of surgical robot system, leading to the efficiency of surgical OR.

Bilateral coordination control of flexible master–slave manipulators using a partial differential equation model

In this study, we evaluate the coordination tracking control problem of a flexible master–slave teleoperation system. The system under consideration is based on a dynamic model described by a set of partial differential equations. Existing research on bilateral controllers is based on teleoperation systems composed of rigid master robots and rigid or flexible slave robots. In this work, we consider teleoperation systems with flexible master and slave robots. We dynamically model flexible master–slave manipulators using partial differential equations. Based on the dynamic model, a bilateral coordination controller is developed to realize the coordination angle tracking and vibration suppression of flexible master–slave manipulators. The teleoperation system is proven to be asymptotically stable under the control scheme. Numerical simulation results illustrate that the proposed controller is effective.

Twin-driven actuator with multi-layered disc magnetorheological fluid clutches for haptics

Magnetorheological fluids are composite materials made of ferromagnetic particles, medium oils, and several types of additives. We have developed actuation systems for the fine haptic control of master–slave robots. In this study, we proposed a new structure of a magnetorheological fluid–based actuator suitable for haptic devices. For the basic structure of the actuator, we proposed a twin-driven magnetorheological fluid actuator using two multi-layered disc-type magnetorheological fluid clutches for haptics. We conducted performance measures for the magnetorheological fluid clutches for haptics with three commercially available magnetorheological fluids (i.e. 122EG, 132DG, and 140CG from Lord Corp.). The experimental results show that 132DG is a better material for force control. Then, we proposed two types of twin-driven magnetorheological fluid actuators (i.e. link type and belt type) and compared their performance. The results show that the averages of the time constant are 19.1 and 16.1 ms for the link type and belt type, respectively. Furthermore, the averages of torque error are 0.033 and 0.068 N m for the link type and belt type, respectively. However, the belt-type twin-driven magnetorheological fluid actuator is better if a large range of motion is required, while the link-type twin-driven magnetorheological fluid actuator is better if accurate torque control is required.

Disturbance observer enhanced variable gain controller for robot teleoperation with motion capture using wearable armbands

Disturbance observer (DOB) based controller performs well in estimating and compensating for perturbation when the external or internal unknown disturbance is slowly time varying. However, to some extent, robot manipulators usually work in complex environment with high-frequency disturbance. Thereby, to enhance tracking performance in a teleoperation system, only traditional DOB technique is insufficient. In this paper, for the purpose of constructing a feasible teleoperation scheme, we develop a novel controller that contains a variable gain scheme to deal with fast-time varying perturbation, whose gain is adjusted linearly according to human surface electromyographic signals collected from Myo wearable armband. In addition, for tracking the motion of operator’s arm, we derive five-joint-angle data of a moving human arm through two groups of quaternions generated from the armbands. Besides, the radial basis function neural networks and the disturbance observer-based control (DOBC) approaches are fused together into the proposed controller to compensate the unknown dynamics uncertainties of the slave robot as well as environmental perturbation. Experiments and simulations are conducted to demonstrated the effectiveness of the proposed strategy.