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Traditionally, in robotic surface finishing, the entire workpiece is processed at a uniform speed, predetermined by the operator, which does not account for variations in the machinability across different regions of the workpiece. This conventional approach often leads to inefficiencies, especially given the diverse geometrical characteristics of workpieces that could potentially allow for different machining speeds. Our study introduces a region-based approach, which improves surface finishing machining time by allowing variable speeds and directions tailored to each region's specific characteristics. This method leverages a task-oriented strategy integrating robot kinematics and workpiece surface geometry, subdivided by the clustering algorithm. Subsequently, methods for optimization algorithms were developed to calculate each region's optimal machining speeds and directions. The efficacy of this approach was validated through numerical results on two distinct workpieces, demonstrating significant improvements in machining times. The region-based approach yielded up to a 37% reduction in machining time compared to traditional single-direction machining. Further enhancements were achieved by optimizing the workpiece positioning, which, in our case, added up to an additional 16% improvement from the initial position. Validation processes were conducted to ensure the collaborative robot's joint velocities remained within safe operational limits while executing the region-based surface finishing strategy. [ABSTRACT FROM AUTHOR]

Workpiece placement plays a crucial role when performing complex surface machining task robotically. If the feasibility of a robotic task needs to be guaranteed, the maximum available capabilities should be higher than the joint capabilities required for task execution. This can be challenging, especially when performing a complex surface machining task with a collaborative robot, which tend to have lower motion capabilities than conventional industrial robots. Therefore, the kinematic and dynamic capabilities within the robot workspace should be evaluated prior to task execution and optimized considering specific task requirements. In order to estimate maximum directional kinematic capabilities considering the requirements of the surface machining task in a physically consistent and accurate way, the Decomposed Twist Feasibility (DTF) method will be used in this paper. Estimation of the total kinematic performance capabilities can be determined accurately and simply using this method, adjusted specifically for robotic surface machining purposes. In this study, we present the numerical results that prove the effectiveness of the DTF method in identifying the optimal placement of predetermined machining tasks within the robot's workspace that requires lowest possible joint velocities for task execution. These findings highlight the practicality of the DTF method in enhancing the feasibility of complex robotic surface machining operations. [ABSTRACT FROM AUTHOR]

Robot workpiece machining is interesting in industry as it offers some advantages, such as higher flexibility in comparison with the conventional approach based on CNC technology. However, in recent years, we have been facing a strong progressive shift to custom-based manufacturing and low-volume/high-mix production, which require a novel approach to automation via the employment of collaborative robotics. However, collaborative robots feature only limited motion capability to provide safety in cooperation with human workers. Thus, it is highly necessary to perform more detailed robot task planning to ensure its feasibility and optimal performance. In this paper, we deal with the problem of studying kinematic robot performance in the case of such manufacturing tasks, where the robot tool is constrained to follow the machining path embedded on the workpiece surface at a prescribed orientation. The presented approach is based on the well-known concept of manipulability, although the latter suffers from physical inconsistency due to mixing different units of linear and angular velocity in a general 6 DOF task case. Therefore, we introduce the workpiece surface constraint in the robot kinematic analysis, which enables an evaluation of its available velocity capability in a reduced dimension space. Such constrained robot kinematics transform the robot's task space to a two-dimensional surface tangent plane, and the manipulability analysis may be limited to the space of linear velocity only. Thus, the problem of physical inconsistency is avoided effectively. We show the theoretical derivation of the proposed method, which was verified by numerical experiments. [ABSTRACT FROM AUTHOR]

Performing the machining of complex surfaces can be a challenging task for a robot, especially in terms of collaborative robotics, where the available motion capabilities are greatly reduced in comparison with conventional industrial robot arms. It is necessary to evaluate these capabilities prior to task execution, for which we need efficient algorithms, especially in the case of flexible robot applications. To provide accurate and physically consistent information about the maximum kinematic capabilities while considering the requirements of the task, an approach called the Decomposed Twist Feasibility (DTF) method is proposed in this study. The evaluation of the maximum feasible end-effector velocity is based on the idea of decomposition into the linear and angular motion capabilities, considering a typical robot machining task with synchronous linear and angular motion. The proposed DTF method is presented by the well-known manipulability polytope concept. Unlike the existing methods that estimate the kinematic performance capabilities in arbitrarily weighted twist space, or separately in the translation and the rotation subspace, our approach offers an accurate and simple solution for the determination of the total kinematic performance capabilities, which is often highly required, especially in the case of robot machining tasks. The numerical results obtained in this study show the effectiveness of the proposed approach. Moreover, the proposed DTF method could represent suitable kinematic performance criteria for the optimal placement of predefined tasks within the robot workspace. [ABSTRACT FROM AUTHOR]

This paper presents the effectiveness of a time-delay compensation method based on the concept of network disturbance and communication disturbance observer for bilateral tele-operation systems under time-varying delay. The most efficient feature of the compensation method is that it works without time-delay models (model-based time-delay compensation approaches like Smith predictor usually need time-delay models). Therefore, the method is expected to be widely applied to network-based control systems, in which time delay is usually unknown and time varying. In this paper, the validity of the time-delay compensation method in the cases of both constant delay and time-varying delay is verified by experimental results compared with Smith predictor. [ABSTRACT FROM AUTHOR]

Accurate position-tracking control in a belt-driven servomechanism can experience vibrations and large tracking errors due to compliance and elasticity introduced by force transmission through the belt and nonlinear-friction phenomenon. In this paper, a new control algorithm which is based on a sliding-mode control that is able to deal with these problems is proposed. In order to further optimize position-tracking performance, the control scheme has been extended by an asymptotic disturbance observer. It has been proven that robust and vibration-free operation of a linear-belt-driven system can be achieved. The experiments presented in this paper show improved position-tracking error response while maintaining vibration suppression. [ABSTRACT FROM AUTHOR]

The realisation of the ideas of smart factories and sustainable manufacturing can be quickly realised in companies where industrial production is high-volume, low-mix. However, it is more difficult to follow trends toward industry 4.0 in craft industries such as tooling. This kind of work environment is a challenge for the deployment of sustainability and smart technologies because many stages involve the so-called "manual processing according to the worker's feeling and experience." With the help of literature review and testing in the production environment, we approach the design of a procedure for planning a sustainable technological upgrade of craft production. The best method proved to be a combination of a maturity model, process mapping with flowcharts, critical analysis, and customised evaluation model. Workplace flexibility, as a move towards sustainability, is presented in a laboratory environment on screwing performed by human wearing HoloLens and collaborative robot. [ABSTRACT FROM AUTHOR]

In the serial hybrid electric propulsion system of a small propeller aircraft the battery state of charge is fluctuating due to the diversity of possible power flows. Overwhelming visual information on the cockpit displays, besides requiring visual pilot attention, increases pilot workload, which is undesirable, especially in risky flight situations. Haptic interfaces, on the other hand, can provide intuitive cues that can be applied to enhance and simplify the cockpit. In this paper, we deal with an enhanced power lever stick, which can provide feedback force feel with haptic cues for enhanced information flow between the pilot and the powertrain system. We present selected haptic patterns for specific information related to the fluctuating battery state of charge. The haptic patterns were designed to reduce pilot workload, and for easy use, safe and energy-efficient control of the hybrid electric powertrain system. We focus on the advanced control design for high-performance force feedback required for rendering fine haptic signals, which stimulates the sensitive haptics of a pilot's hand-arm system. The presented control algorithm has been designed by the sliding mode control (SMC) approach in order to provide disturbance rejection and high-fidelity haptic rendering. The proposed control design has been validated on an experimental prototype system. [ABSTRACT FROM AUTHOR]

Advanced motion control applications require smooth and highly accurate high-bandwidth velocity feedback, which is usually provided by an incremental encoder. Furthermore, high sampling rates are also demanded in order to achieve cutting-edge system performance. Such control system performance with high accuracy can be achieved easily by FPGA-based controllers. On the other hand, the well-known MT method for velocity estimation has been well proven in practice. However, its complexity, which is related to the inherent arithmetic division involved in the calculus part of the method, prevents its holistic implementation as a single-chip solution on small-size low-cost FPGAs that are suitable for practical optimized control systems. In order to overcome this obstacle, we proposed a division-less MT-type algorithm that consumes only minimal FPGA resources, which makes it proper for modern cost-optimized FPGAs. In this paper, we present new results. The recursive discrete algorithm has been further optimized, in order to improve the accuracy of the velocity estimation. The novel algorithm has also been implemented on the experimental FPGA board, and validated by practical experiments. The enhanced algorithm design resulted in improved practical performance. [ABSTRACT FROM AUTHOR]

Velocity measurement by an incremental encoder is an important issue for advanced motion control applications such as robotics. In this paper, we deal with a kind of MT-type velocity estimation method. Though the conventional MT method is well known and has been well proven in practice, it requires execution of an arithmetic division operation that prevents an efficient implementation on low-cost FPGA-based control platforms. Thus, we propose a divisionless MT-type algorithm, which can provide a similar performance in velocity estimation accuracy as the conventional method, but requiring significantly less FPGA resources, since it implements only simple arithmetic operations such as addition, subtraction, and multiplication, that can be implemented more easily on the processing hardware. Furthermore, the algorithm is fast in execution, thus, it provides the output in only a few clock cycles. Though the proposed algorithm can be described in a recursive form, the stability of the estimation process is not jeopardized, although it is an important issue in this case. Hence, the algorithm is introduced in a form which assures stability in a wide speed range. We show the implementation of the algorithm on the experimental FPGA platform. The experimental results validated the proposed divisionless MT-type algorithm fully for accurate velocity estimation. [ABSTRACT FROM AUTHOR]