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To provide high torques needed to move a robot’s links, electric actuators are followed by a transmission system with a high transmission rate. For instance, gear ratios of 100:1 are often used in the joints of a robotic manipulator. This results into an actuator with large mechanical impedance (also known as nonback-drivable actuator). This in turn generates high contact forces when collision of the robotic mechanism occur and can cause humans’ injury. Another disadvantage of electric actuators is that they can exhibit overheating when constant torques have to be provided. Comparing to electric actuators, pneumatic actuators have promising properties for robotic applications, due to their low weight, simple mechanical design, low cost and good power-to-weight ratio. Electropneumatically actuated robots usually have better friction properties. Moreover, because of low mechanical impedance, pneumatic robots can provide moderate interaction forces which is important for robotic surgery and rehabilitation tasks. Pneumatic actuators are also well suited for exoskeleton robots. Actuation in exoskeletons should have a fast and accurate response. While electric motors come against high mechanical impedance and the risk of causing injuries, pneumatic actuators exhibit forces and torques which stay within moderate variation ranges. Besides, unlike direct current electric motors, pneumatic actuators have an improved weight-to-power ratio and avoid overheating problems.

The aim of this paper is to analyze a nonlinear optimal control method for electropneumatically actuated robots. A two-link robotic exoskeleton with electropneumatic actuators is considered as a case study. The associated nonlinear and multivariable state-space model is formulated and its differential flatness properties are proven. The dynamic model of the electropneumatic robot is linearized at each sampling instance with the use of first-order Taylor series expansion and through the computation of the associated Jacobian matrices. Within each sampling period, the time-varying linearization point is defined by the present value of the robot’s state vector and by the last sampled value of the control inputs vector. An H-infinity controller is designed for the linearized model of the robot aiming at solving the related optimal control problem under model uncertainties and external perturbations. An algebraic Riccati equation is solved at each time-step of the control method to obtain the stabilizing feedback gains of the H-infinity controller. Through Lyapunov stability analysis, it is proven that the robot’s control scheme satisfies the H-infinity tracking performance conditions which indicate the robustness properties of the control method. Moreover, global asymptotic stability is proven for the control loop. The method achieves fast convergence of the robot’s state variables to the associated reference trajectories, and despite strong nonlinearities in the robot’s dynamics, it keeps moderate the variations of the control inputs.

In this paper, a novel solution has been proposed for the nonlinear optimal control problem of robotic exoskeletons with electropneumatic actuators. As a case study, the dynamic model of a two-link lower-limb robotic exoskeleton with electropneumatic actuators has been considered. The dynamic model of this robotic system undergoes first approximate linearization at each iteration of the control algorithm around a temporary operating point. Within each sampling period, this linearization point is defined by the present value of the robot’s state vector and by the last sampled value of the control inputs vector. The linearization process relies on first-order Taylor series expansion and on the computation of the associated Jacobian matrices. The modeling error which is due to the truncation of higher-order terms from the Taylor series is considered to be a perturbation which is asymptotically compensated by the robustness of the control algorithm. To stabilize the dynamics of the electropneumatically actuated robot and to achieve precise tracking of reference setpoints, an H-infinity (optimal) feedback controller is designed. Actually, the proposed H-infinity controller for the model of the two-link electropneumatically actuated exoskeleton achieves the solution of the associated optimal control problem under model uncertainty and external disturbances. This controller implements a min-max differential game taking place between: (i) the control inputs which try to minimize a cost function which comprises a quadratic term of the state vector’s tracking error and (ii) the model uncertainty and perturbation inputs which try to maximize this cost function. To select the stabilizing feedback gains of this H-infinity controller, an algebraic Riccati equation is being repetitively solved at each time-step of the control method. The global stability properties of the H-infinity control scheme are proven through Lyapunov analysis.

Pneumatic actuators are characterized by high nonlinearities which are due to air compressibility, thermodynamics and valves behavior and thus pneumatic robots require elaborated nonlinear control schemes to ensure their fast and precise positioning. Among the control methods which have been applied to pneumatic robots, one can distinguish differential geometric approaches (Lie algebra-based control, differential flatness theory-based control, nonlinear model predictive control [NMPC], sliding-mode control, backstepping control and multiple models-based fuzzy control). Treating nonlinearities and fault tolerance issues in the control problem of robotic manipulators with electropneumatic actuators has been a nontrivial task.

The novelty of the proposed control method is outlined as follows: preceding results on the use of H-infinity control to nonlinear dynamical systems were limited to the case of affine-in-the-input systems with drift-only dynamics. These results considered that the control inputs gain matrix is not dependent on the values of the system’s state vector. Moreover, in these approaches the linearization was performed around points of the desirable trajectory, whereas in the present paper’s control method the linearization points are related with the value of the state vector at each sampling instance as well as with the last sampled value of the control inputs vector. The Riccati equation which has been proposed for computing the feedback gains of the controller is novel, so is the presented global stability proof through Lyapunov analysis. This paper’s scientific contribution is summarized as follows: (i) the presented nonlinear optimal control method has improved or equally satisfactory performance when compared against other nonlinear control schemes that one can consider for the dynamic model of robots with electropneumatic actuators (such as Lie algebra-based control, differential flatness theory-based control, nonlinear model-based predictive control, sliding-mode control and backstepping control), (ii) it achieves fast and accurate tracking of all reference setpoints, (iii) despite strong nonlinearities in the dynamic model of the robot, it keeps moderate the variations of the control inputs and (iv) unlike the aforementioned alternative control approaches, this paper’s method is the only one that achieves solution of the optimal control problem for electropneumatic robots.

The use of electropneumatic actuation in robots exhibits certain advantages. These can be the improved weight-to-power ratio, the lower mechanical impedance and the avoidance of overheating. At the same time, precise positioning and accurate execution of tasks by electropneumatic robots requires the application of elaborated nonlinear control methods. In this paper, a new nonlinear optimal control method has been developed for electropneumatically actuated robots and has been specifically applied to the dynamic model of a two-link robotic exoskeleton. The benefit from using this paper’s results in industrial and biomedical applications is apparent.

A comparison of the proposed nonlinear optimal (H-infinity) control method against other linear and nonlinear control schemes for electropneumatically actuated robots shows the following: (1) Unlike global linearization-based control approaches, such as Lie algebra-based control and differential flatness theory-based control, the optimal control approach does not rely on complicated transformations (diffeomorphisms) of the system’s state variables. Besides, the computed control inputs are applied directly on the initial nonlinear model of the electropneumatic robot and not on its linearized equivalent. The inverse transformations which are met in global linearization-based control are avoided and consequently one does not come against the related singularity problems. (2) Unlike model predictive control (MPC) and NMPC, the proposed control method is of proven global stability. It is known that MPC is a linear control approach that if applied to the nonlinear dynamics of the electropneumatic robot, the stability of the control loop will be lost. Besides, in NMPC the convergence of its iterative search for an optimum depends on initialization and parameter values selection and consequently the global stability of this control method cannot be always assured. (3) Unlike sliding-mode control and backstepping control, the proposed optimal control method does not require the state-space description of the system to be found in a specific form. About sliding-mode control, it is known that when the controlled system is not found in the input-output linearized form the definition of the sliding surface can be an intuitive procedure. About backstepping control, it is known that it cannot be directly applied to a dynamical system if the related state-space model is not found in the triangular (backstepping integral) form. (4) Unlike PID control, the proposed nonlinear optimal control method is of proven global stability, the selection of the controller’s parameters does not rely on a heuristic tuning procedure, and the stability of the control loop is assured in the case of changes of operating points. (5) Unlike multiple local models-based control, the nonlinear optimal control method uses only one linearization point and needs the solution of only one Riccati equation so as to compute the stabilizing feedback gains of the controller. Consequently, in terms of computation load the proposed control method for the electropneumatic actuator’s dynamics is much more efficient.

This research paper aims to optimize the calibration process for an ABB IRB 120 robot, specifically for robotic orbital milling applications, by introducing and validating the use of the observability index and telescopic ballbar for accuracy enhancement.

The study uses the telescopic ballbar and an observability index for the calibration of an ABB IRB 120 robot, focusing on robotic orbital milling. Comparative simulation analysis selects the O₃ index. Experimental tests, both static and dynamic, evaluate the proposed calibration approach within the robot’s workspace.

The proposed calibration approach significantly reduces circularity errors, particularly in robotic orbital milling, showcasing effectiveness in both static and dynamic modes at various tool center point speeds.

The study focuses on a specific robot model and application (robotic orbital milling), limiting generalizability. Further research could explore diverse robot models and applications.

The findings offer practical benefits by enhancing the accuracy of robotic systems, particularly in precision tasks like orbital milling, providing a valuable calibration method.

While primarily technological, improved robotic precision can have social implications, potentially influencing fields where robotic applications are crucial, such as manufacturing and automation.

This study’s distinctiveness lies in advancing the accuracy and precision of industrial robots during circular motions, specifically tailored for orbital milling applications. The innovative approach synergistically uses the observability index and telescopic ballbar to achieve these objectives.

The purpose of this paper is to achieve optimal climbing control of the gas-insulated switchgear (GIS) robot, as the authors know that the GIS inspection robot is a kind of artificial intelligent mobile equipment which auxiliary or even substitute human labor drive on the inner wall of the gas-insulated metal enclosed switchgear. The GIS equipment fault inspection and maintenance can be realized through the robot manipulator on the mobile platform and the camera carried on the fuselage, and it is a kind of intelligent equipment for operation. To realize the inspection and operation of the GIS equipment pipeline without blind spots, the robot is required to be able to travel on any wall inside the pipeline, especially the top of the pipeline and both right and left sides of the pipeline, which requires the flexible climbing of the GIS inspection robot. The robot device has a certain adsorption function to ensure that the robot is fully attached to the wall surface. At the same time, the robot manipulator can be used for collision-free obstacle avoidance operation planning in the narrow operation space inside the GIS equipment.

The above two technologies are the key that the robot completes the GIS equipment inspections. Based on this, this paper focuses on modeling and analysis of the chassis adsorption characteristics for the GIS inspection robot. At the same time, the Denavit Hartenberg (D-H) coordinate model of the robot arm system has been established, and the kinematics forward and inverse solutions of the robot manipulator system have been derived.

The reachable working space point cloud diagram of the robot manipulator in MATLAB has been obtained based on the kinematics analysis, and the operation trajectory planning of the robot manipulator using the robot toolbox has been obtained. The simulation results show that the robot manipulator system can realize the movement without collision and obstacle avoidance. The space can cover the entire GIS pipeline so as to achieve no blind area operation.

Finally, the GIS inspection robot physical prototype system has been developed through system integration design, and the inspection, maintenance operation experiment has been carried out in the actual GIS equipment. The entire robot system can complete the GIS equipment inspection operation soundly and improve the operation efficiency. The research in this paper has important theoretical significance and practical application value for the optimization design and practical research of the GIS inspection robot system.

The heterogeneous character of Industry 4.0 opens opportunities for studies to understand the difficulties and challenges found in the transformation process of manufacturers. This article aims to present a critical analysis of the modernization process of an Industry 3.0 automated cell into a fully autonomous cell of Industry 4.0. The objective is to elucidate the difficulties found in this transition process and the possible ways to overcome the challenges, focusing on the management perspective.

For this, the needed steps for the technology transition were defined and the main I4.0 enabling technologies were applied, such as the application of machine learning algorithms to control quality parameters in milling.

The main challenges found were related to the obsolescence of the equipment present in the cell, challenges in data integration and communication protocols, in addition to the training of people who work actively in the project team. The difficulties faced were discussed based on similar studies in the literature and possible solutions for each challenge.

This understanding of possible barriers in the modernization process, and the step-by-step defined for this transition, can be important references for professionals working in manufacturing industries and researchers who aim to deepen their studies in this important and disruptive stage of world industrialization.

Soft robots are known for their excellent safe interaction ability and promising in surgical applications for their lower risks of damaging the surrounding organs when operating than their rigid counterparts. To explore the potential of soft robots in cardiac surgery, this paper aims to propose an adaptive iterative learning controller for tracking the irregular motion of the beating heart.

In continuous beating heart surgery, providing a relatively stable operating environment for the operator is crucial. It is highly necessary to use position-tracking technology to keep the target and the surgical manipulator as static as possible. To address the position tracking and control challenges associated with dynamic targets, with a focus on tracking the motion of the heart, control design work has been carried out. Considering the lag error introduced by the material properties of the soft surgical robotic arm and system delays, a controller design incorporating iterative learning control with parameter estimation was used for position control. The stability of the controller was analyzed and proven through the construction of a Lyapunov function, taking into account the unique characteristics of the soft robotic system.

The tracking performance of both the proportional-derivative (PD) position controller and the adaptive iterative learning controller are conducted on the simulated heart platform. The results of these two methods are compared and analyzed. The designed adaptive iterative learning control algorithm for position control at the end effector of the soft robotic system has demonstrated improved control precision and stability compared with traditional PD controllers. It exhibits effective compensation for periodic lag caused by system delays and material characteristics.

Tracking the beating heart, which undergoes quasi-periodic and complex motion with varying accelerations, poses a significant challenge even for rigid mechanical arms that can be precisely controlled and makes tracking targets located at the surface of the heart with the soft robot fraught with considerable difficulties. This paper originally proposes an adaptive interactive learning control algorithm to cope with the dynamic object tracking problem. The algorithm has theoretically proved its convergence and experimentally validated its performance at the cable-driven soft robot test bed.

The purpose of this paper is to propose a casting process for the production of double-chamber soft fingers, which avoids the problems of air leakage and fracture caused by multistep casting. This proposed method facilitates the simultaneous casting of the inflation chamber and the jamming chamber.

An integrated molding technology based on the lost wax casting method is proposed for the manufacture of double-chamber soft fingers. The solid wax core is assembled with the mold, and then liquid silicone rubber is injected into it. After cooling and solidification, the mold is stripped off and heated in boiling water, so that the solid wax core melts and precipitates, and the integrated soft finger is obtained.

The performance and fatigue tests of the soft fingers produced by the proposed method have been carried out. The results show that the manufacturing method can significantly improve the fatigue resistance and stability of the soft fingers, while also avoiding the problems such as air leakage and cracking.

The improvement of the previous multistep casting method of soft fingers is proposed, and the integrated molding manufacturing method is proposed to avoid the problems caused by secondary bonding.

The introduction of robots as value-adding “workers” on the shop floor triggers complex changes to manufacturing work. Such changes involve highly entangled relationships between technology, organisation and people. Understanding such entanglements requires a holistic assessment of contemporary robotised manufacturing work, to anticipate the dynamically emerging opportunities and risks of robotised work.

A systematic literature review of 87 papers was conducted to capture relevant themes of change in robotised manufacturing work. The literature was analysed using a thematic analysis approach, with Checkland’s soft systems thinking as an analytical framework.

Based on the literature analysis, the authors present a systemic conceptualisation of robotised manufacturing work. Specifically, the conceptualisation highlights four entangled themes of change: work, organisation of labour, workers’ (experiences) and the firm’s environment. Moreover, the authors discuss the complex patterns of interactions between these objects as relationships that defy straightforward cause–effect models.

The findings draw attention to complex interactions between robotisation and manufacturing work. It can, therefore, inform strategic decisions and support projects for robotisation from a holistic perspective.

The authors present a novel approach to studying and designing robotised manufacturing work as a conceptual system. In particular, the paper shifts the focus towards crucial properties of the system, which are subject to complex changes alongside the introduction of robot technology in manufacturing. Soft systems thinking enables new research avenues to explain complex phenomena at the intersection of robotisation and manufacturing work.

In complex environments, a spherical robot has great application value. When the pendulum spherical robot is stopped or disturbed, there will be a periodic oscillation. This situation will seriously affect the stability of the spherical robot. Therefore, this paper aims to propose a control method based on backstepping and disturbance observers for oscillation suppression.

This paper analyzes the mechanism of oscillation. The oscillation model of the spherical robot is constructed and the relationship between the oscillation and the internal structure of the sphere is analyzed. Based on the oscillation model, the authors design the oscillation suppression control of the spherical robot using the backstepping method. At the same time, a disturbance observer is added to suppress the disturbance.

It is found that the control system based on backstepping and disturbance observer is simple and efficient for nonlinear models. Compared with the PID controller commonly used in engineering, this control method has a better control effect.

The proposed method can provide a reliable and effective stability scheme for spherical robots. The problem of instability in real motion is solved.

In this paper, the oscillation model of a spherical robot is innovatively constructed. Second, a new backstepping control method combined with a disturbance observer for the spherical robot is proposed to suppress the oscillation.

The study aims to equip robots with the ability to precisely maintain interaction forces, which is crucial for tasks such as polishing in highly dynamic environments with unknown and varying stiffness and geometry, including those found in airplane wings or thin, soft materials. The purpose of this study is to develop a novel adaptive force-tracking admittance control scheme aimed at achieving a faster response rate with higher tracking accuracy for robot force control.

In the proposed method, the traditional admittance model is improved by introducing a pre-proportional-derivative controller to accelerate parameter convergence. Subsequently, the authors design an adaptive law based on fuzzy logic systems (FLS) to compensate for uncertainties in the unknown environment. Stability conditions are established for the proposed method through Lyapunov analysis, which ensures the force tracking accuracy and the stability of the coupled system consisting of the robot and the interaction environment. Furthermore, the effectiveness and robustness of the proposed control algorithm are demonstrated by simulation and experiment.

A variety of unstructured simulations and experimental scenarios are designed to validate the effectiveness of the proposed algorithm in force control. The outcomes demonstrate that this control strategy excels in providing fast response, precise tracking accuracy and robust performance.

In real-world applications spanning industrial, service and medical fields where accurate force control by robots is essential, the proposed method stands out as both practical and straightforward, delivering consistently satisfactory performance across various scenarios.

This research introduces a novel adaptive force-tracking admittance controller based on FLS and validated through both simulations and experiments. The proposed controller demonstrates exceptional performance in force control within environments characterized by unknown and varying.

The purpose of this review is to comprehensively consider the material properties and processing of additive titanium alloy and provide a new perspective for the robotic grinding and polishing of additive titanium alloy blades to ensure the surface integrity and machining accuracy of the blades.

At present, robot grinding and polishing are mainstream processing methods in blade automatic processing. This review systematically summarizes the processing characteristics and processing methods of additive manufacturing (AM) titanium alloy blades. On the one hand, the unique manufacturing process and thermal effect of AM have created the unique processing characteristics of additive titanium alloy blades. On the other hand, the robot grinding and polishing process needs to incorporate the material removal model into the traditional processing flow according to the processing characteristics of the additive titanium alloy.

Robot belt grinding can solve the processing problem of additive titanium alloy blades. The complex surface of the blade generates a robot grinding trajectory through trajectory planning. The trajectory planning of the robot profoundly affects the machining accuracy and surface quality of the blade. Subsequent research is needed to solve the problems of high machining accuracy of blade profiles, complex surface material removal models and uneven distribution of blade machining allowance. In the process parameters of the robot, the grinding parameters, trajectory planning and error compensation affect the surface quality of the blade through the material removal method, grinding force and grinding temperature. The machining accuracy of the blade surface is affected by robot vibration and stiffness.

This review systematically summarizes the processing characteristics and processing methods of aviation titanium alloy blades manufactured by AM. Combined with the material properties of additive titanium alloy, it provides a new idea for robot grinding and polishing of aviation titanium alloy blades manufactured by AM.