Search Results (69)

This paper presents a control method for achieving precise robotic contact on complex and curved surfaces in manufacturing and automation. The method combines smooth trajectory planning with contact force control to improve finishing accuracy while reducing processing time. It integrates a Bézier curve with a simplified hexic polynomial implemented through a position-based impedance controller that is enhanced by a novel force corrector unit. The model is referred to as the Adaptive Bézier–Based Impedance Constant Force Controller (ABBIFC), where the Bézier curve length is calculated using Simpson’s rule, and surface orientations are interpolated using quadratic quaternions. A hexic polynomial velocity profile ensures consistent motion speed throughout the process. This method effectively regulates both contact force and positional accuracy, resulting in high-quality surface finishes. Simulation studies and real-time polishing experiments demonstrate the system’s capability to accurately track path, speed, and force, with significantly reduced force errors. This approach advances robotic automation in applications such as polishing, grinding, and other surface finishing tasks by ensuring smooth motion and precise force control. Full article

Objective: The primary objective of this study was to evaluate the evolution of surgical approaches in the management of endometrial cancer in Polish tertiary referral hospitals, comparing the use of minimally invasive surgery (MIS) and laparotomy in 2023 versus 2013. Methods: This retrospective observational study analyzed data from tertiary referral centers in Poland. All surgeries performed for apparently early-stage endometrial cancer in 2013 and 2023 were included. Results: A total of 1062 patients were analyzed, with 417 undergoing operations in 2013 and 640 in 2023. In 2013, 92.6% (386/417) of patients underwent laparotomy. By 2023, 80.1% (513/640) of patients were treated using minimally invasive approaches, including laparoscopy (56.2%, 362/640), robotic-assisted laparoscopy (21.7%, 139/640), and vaginal surgery (1.9%, 12/640). No conversions to laparotomy were recorded in 2013. In 2023, 22 conversions occurred—21 in the laparoscopy group (5.8%, 21/362) and one in the vaginal surgery group (8.3%, 1/12). No conversions were reported in the robotic-assisted group. Intraoperative complications were observed in 2.2% (8/362) of laparoscopic cases, and postoperative complications in 4.4% (16/362). In the robotic-assisted group, one intraoperative complication (0.7%) was reported, with no postoperative complications. Conclusions: Over the past decade, there has been a significant shift in the surgical management of endometrial cancer in Poland, with a growing preference for minimally invasive surgery (MIS). The rate of conversion from MIS to laparotomy remains below 6%. Robotic-assisted laparoscopic surgery may offer additional benefits, particularly for obese patients. Full article

This study proposes a systematic solution to the motion planning challenges in dual-robot collaborative grinding and polishing systems, with its effectiveness experimentally validated. By establishing a dual-robot pose constraint model, this study innovatively integrates the “handshake” method with the seven-point calibration approach, achieving enhanced spatial mapping accuracy between the base coordinate system and tool coordinate system. Based on the modified Denavit–Hartenberg (DH) method, this study establishes kinematic modeling for EPSON C4-A901S robots on the MATLAB platform. By integrating calibration parameters, a dual-robot collaborative grinding model is constructed, with its reliability thoroughly verified through comprehensive simulations. An experimental platform integrating dual EPSON C4-series robots with grinding devices, clamping fixtures, and drive systems was established. The average error below 8 mm from 10 repeated experiments fully validates the accuracy and practical applicability of the integrated calibration method. Full article

Digital twin (DT) is a useful tool for the remote monitoring, analyzing, controlling, etc. of industrial equipment in a harsh working environment unfriendly to human workers. Although much research has been devoted to DT modeling methods, there are still limitations. For example, (1) existing DT modeling methods are usually focused on specific types of equipment rather than being generally applicable to different types of equipment and requirements. (2) Existing DT models usually emphasize working condition monitoring and have relatively limited capability for modeling the operation and maintenance mechanism of the equipment for further decision making. (3) How to integrate artificial intelligence algorithms into DT models still requires further exploration. In this regard, a systematic and general DT modeling method is proposed for the remote monitoring and intelligent maintenance of industrial equipment. The DT model contains a multi-modal digital model, a multi-layer status model, and an intelligent interaction model driven by a kind of human-readable/computer-deployable event-state knowledge graph. Using the model, the dynamic workflows, working mechanisms, working status, workpiece logistics, monitoring data, and intelligent functions, etc., during the remote monitoring and maintenance of industrial equipment can be realized. The model was verified through three different DT modeling scenarios of a robot-based carbon block polishing processing line. Full article

Robotic polishing is crucial for achieving superior surface finishes in manufacturing. However, precise force control presents significant challenges, particularly for curved workpieces exhibiting time-varying stiffness. Traditional methods typically struggle to adapt to these dynamic conditions, often leading to inconsistent results and suboptimal surface quality. This study proposes an Adaptive Impedance Control based on Visual Guidance (AICVG) strategy for robotic polishing. This approach integrates real-time visual feedback for geometric perception and adaptive tool path generation with a fuzzy logic system that dynamically adjusts impedance parameters to account for unforeseen surface stiffness variations. Simulations and experimental validations conducted on a robotic platform demonstrate that the AICVG strategy significantly outperforms both traditional impedance control and conventional fuzzy logic-based adaptive impedance control. Specifically, it maintains force control errors within ±1.5 N under dynamic stiffness conditions and achieves a 60% reduction in workpiece surface roughness compared to the aforementioned alternative methods. This study presents a robust and precise control framework that significantly enhances the adaptability and efficacy of robotic polishing for complex geometries, thereby advancing automated solutions in high-precision manufacturing. Full article

Free-form surface polishing is a key process in precision machining within high-end manufacturing, where optimizing the polishing trajectory directly influences both processing quality and efficiency. Traditional trajectory planning methods for free-form surface polishing in high-curvature regions suffer from issues such as a lack of precision, low trajectory continuity, and inefficiency. This paper proposes an improved trajectory planning method based on curvature characteristics, incorporating dynamic partitioning and boundary smoothing algorithms. These methods dynamically adjust according to surface curvature, enhancing processing efficiency and surface quality. Additionally, a hybrid optimization framework combining a genetic algorithm (GA) and local search (LS) is proposed to address the challenges of balancing global optimization with local fine-tuning in traditional trajectory planning methods. These challenges often result in large errors, low machining efficiency, and unstable surface quality. The method optimizes the overall trajectory distribution through a global search using GA while locally refining the high-curvature regions with LS. This combination improves trajectory uniformity and smoothness, and the results demonstrate significant increases in machining efficiency and accuracy. Finally, the feasibility of the trajectory planning method was verified through motion simulation. This paper also provides a detailed description of the mathematical modeling, algorithm implementation, and simulation analysis of the XY-3-RPS hybrid robot for trajectory optimization, offering both a theoretical foundation and engineering support for its application in free-form surface polishing. Full article

The removal of rust from large equipment such as trains and ship hulls poses a significant challenge. Traditional methods, such as chemical cleaning, flame rust removal, and laser rust removal, suffer from drawbacks such as high energy consumption, operational complexity, and poor mobility. Sandblasting and high-pressure water jet rust removal face issues such as high consumable costs and environmental pollution. Existing robotic grinding systems often rely on precise measurement of the workpiece surface geometry to perform deburring and polishing tasks; however, they lack the sufficient adaptability and robustness required for rust removal operations. To address these limitations, this study proposes a floating grinding actuator scheme based on compound force-position fuzzy control. By implementing simplified path-point planning, continuous grinding and rust removal can be achieved without requiring the pre-measurement of workpiece geometry data. This solution integrates force and laser displacement sensors to provide real-time compensation for path deviations and ensures adaptability to complex surfaces. A fuzzy derivative-leading PID algorithm was employed to control the grinding force, enabling adaptive force regulation and enhancing the control precision. Rust removal test results demonstrate that under varying advancing speeds, fuzzy derivative-leading PID control can significantly reduce fluctuations in both the grinding force and average error compared to traditional PID control. At a speed of 40 mm/s, excellent control performance was maintained, achieving a rust removal rate of 99.73%. This solution provides an efficient, environmentally friendly, and high-precision automated approach to rust removal using large-scale equipment. Full article

Pneumatic polishing tools are commonly used in traditional robot mold polishing systems, but they have problems with the stable control of mold surface roughness due to low precision and poor adaptability in polishing force adjustment. The integration of an adaptive hydraulic polishing (AHP) tool and robot system effectively solves the above problems, providing a robust solution for the high-precision polishing of various molds. This study systematically investigates the robotic polishing of NAK80 mold steel using an AHP-equipped robotic platform with 3M abrasive discs of progressively refined grit sizes (P180, P400, P800). Through single-factor experiments and response surface methodology, the effects of polishing force, rotational speed, and feeding speed on surface roughness were quantitatively analyzed. The relationship between surface roughness and the polishing parameters was derived to elucidate the roughness evolution before and after over-polishing. Orthogonal experiments combined with range analysis identified optimal parameter combinations for P180 (20 N polishing force, 5000 RPM rotational speed, and 5 mm·s⁻¹ feeding speed) and P400 abrasives (10 N polishing force, 4000 RPM rotational speed, and 5 mm·s⁻¹ feeding speed), achieving minimum surface roughness values of 0.08 µm and 0.044 µm, respectively. For P800 abrasives, a central composite design was used to develop a roughness prediction model with a ≤7.14% relative error, and the optimal parameters are a 20 N polishing force, a 5000 RPM rotational speed, and a 5 mm·s⁻¹ feeding speed. The sequential application of the optimized parameters across all the grit sizes can reduce the surface roughness from an initial 0.4 µm to a final 0.017 µm, representing a 95.75% improvement in the surface finish. Full article

Pneumatic force control has a broad application background in the automation field, such as in industrial polishing, robotic grasping, and humanoid robots. Nonlinear hysteresis characteristics are one of the major factors that affect the feedforward force control performance of a pneumatic system. The primary motivation of this paper is to develop an accurate feedforward actuating force control method for a single-acting pneumatic cylinder with a nonlinear hysteresis characteristic. A data-driven neural network modeling method is presented to achieve accurate actuating force modeling. The modeling accuracy of the neural network model under different configurations of the input layer is quantitatively analyzed to determine the essential modeling variables. The real-time execution speed of neural network models with different numbers of hidden neurons is evaluated to achieve a balance between the modeling accuracy and the real-time computing speed of the neural network model. Then, a single-acting pneumatic system is fabricated to experimentally verify the effectiveness of the proposed modeling and control method. The experimental results reveal that the actuating force can achieve ideal tracking of the target. In both the loading and the unloading process, the amplitude of the control error is less than 0.5 N. The overall RMS value of the control error is about 1 N. An instruction smoothing operation could reduce the percentage overshoot and steady-state error of the feedforward step actuating force control. Full article

The accuracy and stability of robotic systems are significantly influenced by joint clearances, especially in precision applications like optical mirror polishing. This study focuses on a 5-DOF (Degree of Freedom) parallel manipulator designed for optical mirror polishing. The study conducts dynamic modeling by incorporating prismatic joint clearance and examines the resulting dynamic response. Previous studies on dynamic modeling have primarily focused on planar mechanisms with rotational or ball joint clearances, whereas research on parallel manipulators with spatial prismatic joint clearances remains limited. This study introduces a comprehensive dynamic modeling framework for parallel manipulators with prismatic joint clearance, utilizing the Lagrange multiplier method (LMD). First, the prismatic joint models of the guideway and slider in the parallel manipulator are simplified, enabling the determination of different contact states and the calculation of friction and contact forces for various contact types. Second, the dynamic equations of the parallel manipulator are derived by establishing system constraint equations. Finally, the dynamic responses of various clearance-related factors are determined through a combination of theoretical calculations and ADAMS simulations. This study provides a framework for modeling the dynamics of parallel manipulators with prismatic joint gaps, offering valuable insights into the design and control of high-precision robotic systems. Full article

Trajectory planning is essential for robotic polishing tasks, as the effectiveness of this planning directly influences the quality of the work and the energy efficiency of the operation. This study introduces an innovative trajectory planning method for robotic polishing tasks, focusing on the development and application of quintic B-spline interpolation. Recognizing the critical impact of trajectory planning on the quality and energy efficiency of robotic operations, we analyze the structure and parameters of the ABB-IRB120 robot within a laboratory setting. Using the Denavit–Hartenberg parameter method, a kinematic model is established, and the robot’s motion equations are derived through matrix transformation. We then propose a novel approach by implementing both fifth-degree polynomial and quintic B-spline interpolation algorithms for planning the robot’s spatial spiral arc trajectory, which is a key contribution of this work. The effectiveness of these methodologies is validated through simulation in MATLAB’s robotics toolbox. Our findings demonstrate that the quintic B-spline interpolation not only significantly improves task precision but also optimizes energy consumption, making it a superior method for trajectory planning in robotic grinding applications. By integrating advanced interpolation techniques, this study provides substantial technological and environmental benefits, offering a groundbreaking reference for enhancing the precision and efficiency of robotic control systems. Full article

Six-degree-of-freedom industrial robots, known for their low cost and high flexibility, have been extensively applied in optical processing. Precise pose control in robot-based optical processing systems depends on the accurate calibration of the tool coordinate system. However, in robot magnetorheological finishing (Robot-MRF) systems, the spherical shape of the polishing wheel poses significant challenges in precisely identifying the working point on the tool’s surface. Traditional calibration methods, such as the four-point or six-point techniques, fail to accurately calibrate the tool coordinate system for MRF tools. To overcome this limitation, a laser tracker-based calibration method is proposed for parameter calibration of the Robot-MRF system. Experimental results show that this method achieves a maximum repeatability error of just 0.0505 mm, significantly improving the stability and reliability of the calibration results and meeting the high-precision processing requirements of MRF technology. Full article

Newly developed Sol–gel (SG) flexible tools are used to polish complex marble surfaces with a robot to achieve a high-gloss, low-roughness, and scratch-free surface. The SG tool is composed of semi-solid abrasive and flexible fiber pads, which can realize a dual yielding effect at both the micro and macro levels so that the SG flexible tool can better fit the complex curved surface. Through the simulation analysis of the contact of SG flexible tools, the relationship between different curvature surfaces and polishing forces was obtained. Based on the Preston material removal theory, constant-pressure polishing of surfaces of different curvatures was achieved by simulating the contact force distribution between the SG flexible tool and the marble surface, as well as the constant-pressure material removal profile. By optimizing the space of the polishing trajectory, the uniformity of the material removal depth was improved, and the consistency of surface quality after polishing was enhanced. By establishing a model that correlates the optimum polishing trajectory space with curvature for surfaces of different curvatures, the effective prediction of material removal profiles for robotic polishing of surfaces of different curvatures was achieved. These strategies aim to ensure surface consistency after polishing complex curved surfaces under different conditions, thereby increasing the product’s added value. This research provides initial theoretical guidance for the application of SG flexible tools in the robotic polishing of marble with complex curved surfaces. Full article

Emotion recognition by social robots is a serious challenge because sometimes people also do not cope with it. It is important to use information about emotions from all possible sources: facial expression, speech, or reactions occurring in the body. Therefore, a multimodal emotion recognition system was introduced, which includes the indicated sources of information and deep learning algorithms for emotion recognition. An important part of this system includes the speech analysis module, which was decided to be divided into two tracks: speech and text. An additional condition is the target language of communication, Polish, for which the number of datasets and methods is very limited. The work shows that emotion recognition using a single source—text or speech—can lead to low accuracy of the recognized emotion. It was therefore decided to compare English and Polish datasets and the latest deep learning methods in speech emotion recognition using Mel spectrograms. The most accurate LSTM models were evaluated on the English set and the Polish nEMO set, demonstrating high efficiency of emotion recognition in the case of Polish data. The conducted research is a key element in the development of a decision-making algorithm for several emotion recognition modules in a multimodal system. Full article

Force control is one of the core modules for surface finishing such as grinding, polishing and sanding. However, the current force control methods based on human skills lack in-depth analysis of data patterns or are only applicable to flat surfaces. In addition, surface finishing is mainly performed by hand, resulting in low processing efficiency and poor product consistency. Therefore, this paper proposes a force control method that incorporates human skills to achieve relatively accurate force skill transfer and complex surface finishing. Firstly, human skills consisting of the force skill and the motion skill are learned. The force skill is used to generate the desired force. Then, a series of discrete poses are obtained based on human demonstration and combined with the motion skill to generate the desired trajectory. Finally, a computed-torque impedance control method is proposed to achieve relatively accurate force skill transfer and complex surface finishing by incorporating the desired trajectory and the desired force. The experiments are conducted on a platform composed of a 7-DOF collaborative robot manipulator from Franka Emika and a complex violin surface. The results demonstrate that the proposed force control method can achieve relatively accurate force skill transfer and improve the surface quality of the workpiece. Full article