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This article aims at investigating the global stiffness optimization of a Tricept manipulator and the multi-objective optimization of global stiffness and well-conditioned workspace for 3SPS-S manipulator. Firstly, the genetic algorithm is used to optimize the sum of mean value and the standard deviation of leading diagonal elements of the compliance matrix of the Tricept manipulator to obtain the maximum global stiffness. Secondly, the sum of mean value and standard deviation of leading diagonal elements of the compliance matrix of the 3SPS-S manipulator was used to evaluate the global stiffness and the global condition index was used to evaluate the workspace. The global stiffness and well-conditioned workspace of the 3SPS-S mechanism were optimized simultaneously based on Pareto front theory, and the results show that the stiffness and workspace have increased after optimization.

The purpose of this study is to plan and develop a cost-effective health-care robot for assisting and observing the patients in an accurate and effective way during pandemic situation like COVID-19. The purposed research work can help in better management of pandemic situations in rural areas as well as developing countries where medical facility is not easily available.

It becomes very difficult for the medical staff to have a continuous check on patient’s condition in terms of symptoms and critical parameters during pandemic situations. For dealing with these situations, a service mobile robot with multiple sensors for measuring patients bodily indicators has been proposed and the prototype for the same has been developed that can monitor and aid the patient using the robotic arm. The fuzzy controller has also been incorporated with the mobile robot through which decisions on patient monitoring can be taken automatically. Mamdani implication method has been utilized for formulating mathematical expression of M number of “if and then condition based rules” with defined input X_j (j = 1, 2, ………. s), and output y_i. The inputs and output variables are formed by the membership functions µ_Aij(x_j) and µ_Ci(y_i) to execute the Fuzzy Inference System controller. Here, Aij and Ci are the developed fuzzy sets.

The fuzzy-based prediction model has been tested with the output of medicines for the initial 27 runs and was validated by the correlation of predicted and actual values. The correlation coefficient has been found to be 0.989 with a mean square error value of 0.000174, signifying a strong relationship between the predicted values and the actual values. The proposed research work can handle multiple tasks like online consulting, continuous patient condition monitoring in general wards and ICUs, telemedicine services, hospital waste disposal and providing service to patients at regular time intervals.

The novelty of the proposed research work lies in the integration of artificial intelligence techniques like fuzzy logic with the multi-sensor-based service robot for easy decision-making and continuous patient monitoring in hospitals in rural areas and to reduce the work stress on medical staff during pandemic situation.

The idea is to exploit the natural stability and performance of the human arm during movement, execution and manipulation. The purpose of this paper is to remotely control a handling robot with a low cost but effective solution.

The developed approach is based on three different techniques to be able to ensure movement and pattern recognition of the operator’s arm as well as an effective control of the object manipulation task. In the first, the methodology works on the kinect-based gesture recognition of the operator’s arm. However, using only the vision-based approach for hand posture recognition cannot be the suitable solution mainly when the hand is occluded in such situations. The proposed approach supports the vision-based system by an electromyography (EMG)-based biofeedback system for posture recognition. Moreover, the novel approach appends to the vision system-based gesture control and the EMG-based posture recognition a force feedback to inform operator of the real grasping state.

The main finding is to have a robust method able to gesture-based control a robot manipulator during movement, manipulation and grasp. The proposed approach uses a real-time gesture control technique based on a kinect camera that can provide the exact position of each joint of the operator’s arm. The developed solution integrates also an EMG biofeedback and a force feedback in its control loop. In addition, the authors propose a high-friendly human-machine-interface (HMI) which allows user to control in real time a robotic arm. Robust trajectory tracking challenge has been solved by the implementation of the sliding mode controller. A fuzzy logic controller has been implemented to manage the grasping task based on the EMG signal. Experimental results have shown a high efficiency of the proposed approach.

There are some constraints when applying the proposed method, such as the sensibility of the desired trajectory generated by the human arm even in case of random and unwanted movements. This can damage the manipulated object during the teleoperation process. In this case, such operator skills are highly required.

The developed control approach can be used in all applications, which require real-time human robot cooperation.

The main advantage of the developed approach is that it benefits at the same time of three various techniques: EMG biofeedback, vision-based system and haptic feedback. In such situation, using only vision-based approaches mainly for the hand postures recognition is not effective. Therefore, the recognition should be based on the biofeedback naturally generated by the muscles responsible of each posture. Moreover, the use of force sensor in closed-loop control scheme without operator intervention is ineffective in the special cases in which the manipulated objects vary in a wide range with different metallic characteristics. Therefore, the use of human-in-the-loop technique can imitate the natural human postures in the grasping task.

Mooring chains used to stabilise offshore floating platforms are often subjected to harsh environmental conditions on a daily basis, i.e. high tidal waves, storms, etc. Therefore, the integrity assessment of chain links is vital, and regular inspection is mandatory for offshore structures. The development of chain climbing robots is still in its infancy due to the complicated climbing structure presented by mooring chains. The purpose of this paper is to establish an automated climbing technique for mooring chain inspection.

This paper presents a Cartesian legged tracked-wheel crawler robot developed for mooring chain inspection. The proposed robot addresses the misalignment condition of the mooring chains which is commonly evident in in situ conditions.

The mooring chain link misalignment is investigated mathematically and used as a design parameter for the proposed robot. The robot is validated with laboratory-based climbing experiments.

Chain breaking can lead to vessel drift and serious damage such as riser rupture, production shutdown and hydrocarbon release. Currently, structural health monitoring of chain links is conducted using either remotely operated vehicles which come at a high cost or by manual means which increase the danger to human operators. The robot can be used as a platform to convey equipment, i.e. tools for non-destructive testing/evaluation applications.

This study has upgraded a previously designed magnetic adhesion tracked-wheel mooring chain climbing robot to address the misalignment issues of operational mooring chains. As a result of this study, the idea of an orthogonally placed Cartesian legged-magnetic adhesion tracked wheel robotic platform which can eliminate concerns related to the misaligned mooring chain climbing has been established.

The purpose of this paper is to establish analytical and numerical solutions of a navigational law to estimate displacements of hyper-static multi-legged mobile robots, which combines: monocular vision (optical flow of regional invariants) and legs dynamics.

In this study the authors propose a Euler-Lagrange equation that control legs’ joints to control robot's displacements. Robot's rotation and translational velocities are feedback by motion features of visual invariant descriptors. A general analytical solution of a derivative navigation law is proposed for hyper-static robots. The feedback is formulated with the local speed rate obtained from optical flow of visual regional invariants. The proposed formulation includes a data association algorithm aimed to correlate visual invariant descriptors detected in sequential images through monocular vision. The navigation law is constrained by a set of three kinematic equilibrium conditions for navigational scenarios: constant acceleration, constant velocity, and instantaneous acceleration.

The proposed data association method concerns local motions of multiple invariants (enhanced MSER) by minimizing the norm of multidimensional optical flow feature vectors. Kinematic measurements are used as observable arguments in the general dynamic control equation; while the legs joints dynamics model is used to formulate the controllable arguments.

The given analysis does not combine sensor data of any kind, but only monocular passive vision. The approach automatically detects environmental invariant descriptors with an enhanced version of the MSER method. Only optical flow vectors and robot's multi-leg dynamics are used to formulate descriptive rotational and translational motions for self-positioning.

Stiffness control of redundant robot arm, aimed at using extra degrees of freedom (DoF) to shape the robot tool center point (TCP) elastomechanical behavior to be consistent with the essential requirements needed for a successful part mating process, i.e., to mimic part supporting mechanism with selective quasi-isotropic compliance (Remote Center of Compliance – RCC), with additional properties of inherent flexibility.

Theoretical analysis and synthesis of the complementary projector for null-space stiffness control of kinematically redundant robot arm. Practical feasibility of the proposed approach was proven by extensive computer simulations and physical experiments, based on commercially available 7 DoF SIA 10 F Yaskawa articulated robot arm, equipped with the open-architecture control system, system for generating excitation force, dedicated sensory system for displacement measurement and a system for real-time acquisition of sensory data.

Simulation experiments demonstrated convergence and stability of the proposed complementary projector. Physical experiments demonstrated that the proposed complementary projector can be implemented on the commercially available anthropomorphic redundant arm upgraded with open-architecture control system and that this projector has the capacity to efficiently affect the task-space TCP stiffness of the robot arm, with a satisfactory degree of consistency with the behavior obtained in the simulation experiments.

A novel complementary projector was synthesized based on the adopted objective function. Practical verification was conducted using computer simulations and physical experiments. For the needs of physical experiments, an adequate open-architecture control system was developed and upgraded through the implementation of the proposed complementary projector and an adequate system for generating excitation and measuring displacement of the robot TCP. Experiments demonstrated that the proposed complementary projector for null-space stiffness control is capable of producing the task-space TCP stiffness, which can satisfy the essential requirements needed for a successful part-mating process, thus allowing the redundant robot arm to mimic the RCC supporting mechanism behavior in a programmable manner.

To gain accurate support for large aircraft structures by ball joints in aircraft digital assembly, this paper aims to propose a novel approach based on visual servoing such that the positioner’s ball-socket can automatically and adaptively approach the ball-head fixed on the aircraft structures.

Image moments of circular marker labeled on the ball-head are selected as visual features to control the three translational degrees of freedom (DOFs) of the positioner, where the composite Jacobian matrix is full rank. Kalman–Bucy filter is adopted for its online estimation, which makes the control scheme more flexible without system calibration. A combination of proportional control with sliding mode control is proposed to improve the system stability and compensate uncertainties of the system.

The ball-socket can accurately and smoothly reach its desired position in a finite time (50 s). Positional deviations between the spherical centers of ball-head and ball-socket in the X-Y plane can be controlled within 0.05 mm which meets the design requirement.

The proposed approach has been integrated into the pose alignment system. It has shown great potential to be widely applied in the leading support for large aircraft structures in aircraft digital assembly.

An adaptive approach for accurate support of large aircraft structures is proposed, which possesses characteristics of high precision, high efficiency and excellent stability.

In recent years, owing to the rapidly increasing labor costs, the demand for robots in daily services and industrial operations has been increased significantly. For further applications and human–robot interaction in an unstructured open environment, fast and accurate tracking and strong disturbance rejection ability are required. However, utilizing a conventional controller can make it difficult for the robot to meet these demands, and when a robot is required to perform at a high-speed and large range of motion, conventional controllers may not perform effectively or even lead to the instability.

The main idea is to develop the control law by combining the SMC feedback with the ADRC control architecture to improve the robustness and control quality of a conventional SMC controller. The problem is formulated and solved in the framework of ADRC. For better estimation and control performance, a generalized proportional integral observer (GPIO) technique is employed to estimate and compensate for unmodeled dynamics and other unknown time-varying disturbances. And benefiting from the usage of GPIO, a new SMC law can be designed by synthesizing the estimation and its history.

The employed methodology introduced a significant improvement in handling the uncertainties of the system parameters without compromising the nominal system control quality and intuitiveness of the conventional ADRC design. First, the proposed method combines the advantages of the ADRC and SMC method, which achieved the best tracking performance among these controllers. Second, the proposed controller is sufficiently robust to various disturbances and results in smaller tracking errors. Third, the proposed control method is insensitive to control parameters which indicates a good application potential.

High-performance robot tracking control is the basis for further robot applications in open environments and human–robot interfaces, which require high tracking accuracy and strong disturbance rejection. However, both the varied dynamics of the system and rapidly changing nonlinear coupling characteristic significantly increase the control difficulty. The proposed method gives a new replacement of PID controller in robot systems, which does not require an accurate dynamic system model, is insensitive to control parameters and can perform promisingly for response rapidity and steady-state accuracy, as well as in the presence of strong unknown disturbances.

Presently, 6 Degree of Freedom (6DOF) visual pose measurement methods enjoy popularity in the industrial sector. However, challenges persist in accurately measuring the visual pose of blank and rough metal casts. Therefore, this paper introduces a 6DOF pose measurement method utilizing stereo vision, and aims to the 6DOF pose measurement of blank and rough metal casts.

This paper studies the 6DOF pose measurement of metal casts from three aspects: sample enhancement of industrial objects, optimization of detector and attention mechanism. Virtual reality technology is used for sample enhancement of metal casts, which solves the problem of large-scale sample sampling in industrial application. The method also includes a novel deep learning detector that uses multiple key points on the object surface as regression objects to detect industrial objects with rotation characteristics. By introducing a mixed paths attention module, the detection accuracy of the detector and the convergence speed of the training are improved.

The experimental results show that the proposed method has a better detection effect for metal casts with smaller size scaling and rotation characteristics.

A method for 6DOF pose measurement of industrial objects is proposed, which realizes the pose measurement and grasping of metal blanks and rough machined casts by industrial robots.

With the increasing development of the surgical robots, the opto-mechatronic technologies are more potential in the robotics system optimization. The optic signal plays an important role in opto-mechatronic systems. This paper aims to present a review of the research status on fiber-optic-based force and shape sensors in surgical robots.

Advances of fiber-optic-based force and shape sensing techniques in the past 20 years are investigated and summarized according to different surgical requirement and technical characteristics. The research status analysis and development prospects are discussed.

Compared with traditional electrical signal conduction, the phototransduction provides higher speed transmission, lower signal loss and the immunity to electromagnetic interference in robot perception. Most importantly, more and more advanced optic-based sensing technologies are applied to medical robots in the past two decades because the prominence is magnetic resonance imaging compatibility. For medical robots especially, fiber-optic sensing technologies can improve working security, manipulating accuracy and provide force and shape feedback to surgeon.

This is a new perspective. This paper mainly researches the application of optical fiber sensor according to different surgeries which is beneficial to learn the great potential of optical fiber sensor in surgical robots. By enumerating the research progress of medical robots in optimization design, multimode sensing and advanced materials, the development tendency of fiber-optic-based force and shape sensing technologies in surgical robots is prospected.