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This paper proposes an operation safety early warning system based on LabView (2014, National Instruments Corporation, Austin, TX, USA) for vascular interventional surgery (VIS) robotic system. The system not only provides intuitive visual feedback information for the surgeon, but also has a safety early warning function. It is well known that blood vessels differ in their ability to withstand stress in different age groups, therefore, the operation safety early warning system based on LabView has a vascular safety threshold function that changes in real-time, which can be oriented to different age groups of patients and a broader applicable scope. In addition, the tracing performance of the slave manipulator to the master manipulator is also an important index for operation safety. Therefore, we also transformed the slave manipulator and integrated the displacement error compensation algorithm in order to improve the tracking ability of the slave manipulator to the master manipulator and reduce master–slave tracking errors. We performed experiments “in vitro” to validate the proposed system. According to previous studies, 0.12 N is the maximum force when the blood vessel wall has been penetrated. Experimental results showed that the proposed operation safety early warning system based on LabView combined with operating force feedback can effectively avoid excessive collisions between the surgical catheter and vessel wall to avoid vascular puncture. The force feedback error of the proposed system is maintained between ±20 mN, which is within the allowable safety range and meets our design requirements. Therefore, the proposed system can ensure the safety of surgery.

In vascular interventional surgery, surgeons operate guidewires and catheters to diagnose and treat patients with the assistance of the digital subtraction angiography (DSA). Therefore, the surgeon will be exposed to X-rays for extended periods. To protect the surgeon, the development of a robot-assisted surgical system is of great significance. The displacement tracking accuracy is the most important issue to be considered in the development of the system. In this study, the active disturbance rejection control (ADRC) method is applied to guarantee displacement tracking accuracy. First, the core contents of the proportional–integral–derivative (PID) and ADRC methods are analyzed. Second, comparative evaluation experiments for incremental PID and ADRC methods are presented. The results show that the ADRC method has better performance of than that of the incremental PID method. Finally, the calibration experiments for the ADRC control method are implemented using the master–slave robotic system. These experiments demonstrate that the maximum tracking error is 0.87 mm using the ADRC method, effectively guaranteeing surgical safety.

The welding seam tracking precision is one of the key factors to ensure welding qua ntity. However, when the operator manually manipulate the master robot to control the slave ro bot tracking welding seam used the master- slave robot remote welding system, seam tracking precision does not meet the requirement of the welding quantity, the influence of control param eters on precision of welding seam tracking is unkown. In this article, a master-slave robot rem ote welding system is set up which includes a master robot with 6 degrees of freedom, a compu ter control system, and robot HP3J carrying a welding torch and laser sensor system. The slave robot tracking welding seam was controlled by computer control system and the human operat or via master manipulator. The influence of control parameters (cross deviation, arc length and welding speed) on precision of welding seam tracking was analysed. The experiment results de monstrate the more control parameters of operator, the lower tracking precision, so in order to guarantee a good welding seam tracking effect, the operator should control less parameters.

To enhance adaptability in orchards with taller average tree heights and improve spraying effectiveness on Jinggang pomelo trees, this paper proposes a UAV-UGV cooperative targeted spraying system (UCTSS) and develops a prototype. The UCTSS primarily consists of a UAV and a UGV, networked using the Robot Operating System (ROS). During operation, both the UAV and UGV navigate between tree rows while carrying the spraying module. When the UAV reaches suitable spraying positions, the UGV halts to activate the spraying module, and the UAV performs targeted spraying from top to bottom. The paper employs a master-slave method for basic formation control of the UAV and UGV, resulting in an average tracking error of 0.118 m and a standard deviation of 0.040 m during testing. Additionally, a LiDAR-based targeted spraying detection method is designed and validated through simulation experiments, achieving an accuracy rate of 96% with an average position error of 0.13 m. Field trials in orchards demonstrate that the UCTSS meets stability requirements, with the average tracking error of the UAV measuring 0.158 m during coordinated movement and 0.013 m during spraying. In terms of spraying effectiveness, the UCTSS exhibits higher average droplet density and deposition values at various heights of the same tree compared to the DJI-T50, along with a lower coefficient of variation between levels, resulting in a more uniform spraying effect. The feasibility of the UCTSS is validated, providing a novel approach for orchard protection in areas with taller average tree heights.

Purpose>This study aims to represent a novel closed-form solutions method based on the product of the exponential model to solve the inverse kinematics of a robotic manipulator. In addition, this method is applied to master–slave control of the minimally invasive surgical (MIS) robot.Design/methodology/approach>For MIS robotic inverse kinematics, the closed-form solutions based on the product of the exponential model of manipulators are divided into the RRR and RRT subproblems. Geometric and algebraic constraints are used as preconditions to solve two subproblems. In addition, several important coordinate systems are established on the surgical robot and master–slave mapping strategies are illustrated in detail. Finally, the MIS robot can realize master–slave control by combining closed-form solutions and master–slave mapping strategy.Findings>The simulation of the instrument manipulator based on the RRR and RRT subproblems is executed to verify the correctness of the proposed closed-form solutions. The fact that the accuracy of the closed-form solutions is better than that of the compensation method is validated by the contrastive linear trajectory experiment, and the average and the maximum tracking errors are 0.1388 mm and 0.3047 mm, respectively. In the animal experiment, the average and maximum tracking error of the left instrument manipulator are 0.2192 mm and 0.4987 mm, whereas the average and maximum tracking error of the right instrument manipulator are 0.1885 mm and 0.6933 mm. The successful completion of the animal experiment comprehensively demonstrated the feasibility and reliability of the master–slave control strategy based on the novel closed-form solutions.Originality/value>The proposed closed-form solutions are error-free in theory. The master–slave control strategy is not affected by calculation error when the closed-form solutions are used in the surgical robot. And the accuracy and reliability of the master–slave control strategy are greatly improved.

This paper presents application of Proportional Integral Derivative (PID) and Non-linear PID (NPID) controllers to optimally operate the master slave robotic system. Teleoperation is widely used in different applications, such as surgical robots, underwater vehicles, power lines and even in space. However there are problems in teleoperation systems that may lead to degradation in system performance or even to system instability. This paper presents new and optimal control schemes that can satisfy the required performance, insure system stability and achieve zero tracking error in presence of constant time delay and model approximation. Optimal gains are obtained using the Genetic Algorithm in a systematic way that could be applied to other control schemes. The results proved the effectiveness of both control schemes than the previously applied scheme. The NPID control scheme has better performance, provided position tracking and achieved zero tracking error in less settling time than PID one. The results obtained by the presented control schemes are evaluated based on comparing the system performance using three different types of controllers which are P-like, Genetic PID and Genetic NPID. The study was carried out using MATLAB/SIMULINK 2017a.

This paper presented the mechanical design and control of a lower limb rehabilitation exoskeleton named “the second lower limb rehabilitation exoskeleton (LLRE-II)”. The exoskeleton with a lightweight mechanism comprises a 16-cm stepless adjustable thigh and calf rod. The LLRE-II weighs less than 16 kg and has four degrees of freedom on each leg, including the waist, hip, knee, and ankle, which ensures fitted wear and comfort. Motors and harmonic drives were installed on the joints of the hip and knee to operate the exoskeleton. Meanwhile, master and slave motor controllers were programmed using a Texas Instruments microcontroller (TMS320F28069) for the walking gait commands and evaluation boards (TMS320F28069/DRV8301) of the joints. A self-tuning multiaxis control system was developed, and the performance of the controller was investigated through experiments. The experimental results showed that the mechanical design and control system exhibit adequate performance. Trajectory tracking errors were eliminated, and the root mean square errors reduced from 6.45 to 1.22 and from 4.15 to 3.09 for the hip and knee, respectively.

In this work, we study the problem of a teleoperation master–slave system with error feedback based on sampled versions of the past and present master and slave positions. The sampling interval is the teleoperation delay, and small random fluctuations in the feedback coefficients are considered apart from small random noise in the dynamics. The overall master–slave dynamical system is abstracted into a stochastic delay differential system with random fluctuations in the parameters. This system is transformed into an ordinary stochastic differential system with an infinite-dimensional state vector, and using perturbation theory, integral expressions for the state correlations are obtained in terms of the noise correlations and feedback coefficient fluctuation correlations. We then partially explain how these computations may be used in minimizing the expected value of a cost functional of the state such as the master–slave tracking error energy. Some details about how the underlying delay differential equations for the master–slave dynamics are simulated using the fourth-order Runge–Kutta algorithm are provided. Finally, the simulation experiments are carried out on hardware, i.e., using the actual PHANToM Omni robot and these demonstrate excellent master–slave tracking when sampled teleoperation feedback is given.