Search Results (82)

The objectives of this study were: (1) to identify factors influencing the performance of dairy cows in an automated milking system (AMS); (2) to construct a synthetic robotic adaptability index (RAI) of cows’ adaptation to the AMS; (3) to evaluate the predictive capabilities of traits describing the milking process and RAI; and (4) to compare the predictive power of different modeling approaches. The data on 796 primiparous Polish Holstein–Friesian cows (40,233 milkings) were obtained from the milking robot management system. Milking efficiency (ME), and the average number (AA) and time (AT) of the teat cup attachments and RAI served as predicted variables. Days in milk, and four AMS milking-related and 18 linear conformation traits were used as predictors. The highest predictive ability for ME was achieved with multilayer perceptron (R² = 0.895), followed by linear regression. For AA, AT, and RAI, the highest R² values were obtained for LASSO regression (0.663, 0.642 and 0.670, respectively). The key factors determining milking performance were functional variables, particularly milk flow rate (MilkFlow) and the number of failed milking attempts (Failure), while conformation traits had limited significance. More complex machine learning models do not always lead to improved prediction quality compared to statistical methods, which emphasizes the need for a critical approach to their application in the analysis of production data. Full article

This paper proposes an adaptive residual extended Kalman filter method optimized by a multi-strategy improved parrot optimization algorithm (MIPO-ARKEKF) to improve the kinematic parameter calibration accuracy and efficiency of robotic polishing systems. To address the limitations of the standard extended Kalman filter (EKF), such as truncation-error accumulation during repeated linearization and sensitivity to manually selected noise parameters, an integrated improvement framework is developed. Specifically, a gradient stabilizer based on state-estimation increments is introduced to alleviate estimation degradation caused by accumulated truncation errors, while the proposed MIPO algorithm is employed to adaptively optimize the process and measurement noise covariance matrices, thereby improving the robustness of parameter identification under practical measurement uncertainty. The calibration process is established on the basis of high-precision external measurement data obtained from the robotic polishing system. In benchmark-function tests, MIPO demonstrates superior convergence performance. In physical experiments based on a KUKA KR210 R2700 robot, the proposed MIPO-ARKEKF method reduces the root mean square positioning error from 0.8927 mm to 0.4858 mm, corresponding to a 45.58% improvement in accuracy. Compared with representative hybrid calibration methods, the proposed method achieves comparable compensation accuracy while reducing computation time by 34.88% to 65.08%. Practical polishing experiments on ultra-low-expansion glass lenses further verify that the proposed method effectively improves end-effector trajectory tracking accuracy and polishing quality, providing an efficient solution for high-precision robotic polishing. Full article

This paper presents a fuzzy-based adaptive admittance control (FAAC) framework for position-controlled robots in uncertain contact environments. The proposed FAAC regulates admittance parameters using three fuzzy adaptation maps rather than directly generating robot control inputs. The Mass-Adaptation Fuzzy Map (MAFM) adjusts the dominant virtual mass eigenvalue, the Damper–Mass Ratio Fuzzy Map (DMRFM) adapts the damping-related ratio, and the Rendering-Quality Supervisory Fuzzy Map (RQ-SFM) restricts unsafe low-mass adaptation based on rendering quality and vibration metrics. An energy-tank-based admissibility filter is integrated to preserve passivity during online parameter adaptation and contact transitions. Comparative simulations against a stiffness-adaptive baseline and an ablated mass–damping adaptive baseline under nominal, noisy, and filtered sensing conditions verify the robustness of the proposed architecture. Experiments on a UR10 polishing task further show that the proposed FAAC improves force-tracking consistency and contact-maintenance robustness compared with fixed-parameter AAC baselines and FAAC-M. In particular, the proposed FAAC achieved the lowest force standard deviation of 2.76 N and no contact-loss events, whereas the baseline AAC controllers exhibited force fluctuations associated with abrupt desired stiffness changes during contact. These results demonstrate the effectiveness of FAAC for robust robot–environment interaction under uncertain contact conditions. Full article

Additive manufacturing (AM) enables the fabrication of complex three-dimensional components with embedded internal flow channels, but the as-built inner surfaces often exhibit high roughness and poor surface-quality uniformity, particularly at non-coplanar corner regions such as sharp bends and junctions. Conventional abrasive flow machining (AFM) can improve the overall surface finish of such channels; however, corner regions commonly remain weak-removal zones because of local flow stagnation and insufficient abrasive action. To address this limitation, this study proposes a six-degree-of-freedom (6-DOF) robotic-arm-assisted liquid metal-driven abrasive flow (LM-AF) polishing strategy in which robotic pose regulation is used to guide the liquid metal droplet to designated corner regions while preserving its responsiveness to the electric field. Numerical simulations and conventional AFM experiments on S-shaped and M-shaped spatial channels were first conducted to identify the corner regions as the primary sources of polishing non-uniformity. A robotic posture-control framework was then established through manipulator kinematics, point-cloud-based flow-direction identification, and Rodrigues-matrix-based pose transformation. On this basis, localized secondary polishing was experimentally performed on an S-shaped channel using an AC electric-field-driven liquid-metal abrasive system. The results show that corner-region roughness was significantly reduced and approached the straight-channel benchmark after secondary polishing, demonstrating a marked improvement in inner-surface uniformity. This study provides a practical route for targeted compensation polishing in complex three-dimensional internal channels and offers a new framework for robotic-assisted post-processing of AM-fabricated flow paths. Full article

A non-contact laser polishing method for additively manufactured polymer components with complex three-dimensional geometries is presented, employing a 6-axis robotic system. Robot-guided sample orientation, a quasi-top-hat scanning strategy, and closed-loop temperature control are combined to address curved geometries. On Selective Laser Sintering (SLS)-manufactured Polyamide 12 (PA12) tensile samples with three build orientations and two thicknesses, laser polishing yields up to a 15% increase in tensile strength (Rm) and a 50% increase in elongation at break (A). For 45°-built 5 mm samples, Rm increases from 31.53 MPa to 36.33 MPa and A from 6.52% to 9.8%, approaching the tensile strength reported for optimally oriented SLS-printed PA12 Smooth samples of the same grade. For convex–concave PA12 demonstrators, areal roughness (Sa) on convex surfaces is reduced from 33.6 µm to 2.7 µm (approximately 92%) and the high-pass-filtered micro-roughness (Sa_HP) on concave surfaces by 98.2% to 0.15 µm. For Fused Deposition Modeling (FDM)-printed Polyaryletherketone (PAEK) samples, Sa is reduced from 28.35 µm to 4.1 µm and Sa_HP from 15.98 µm to 0.23 µm (98.6%), despite the high melting temperature and anisotropic raster topography. These results demonstrate that robotic laser polishing constitutes a viable post-processing approach for functionally demanding polymer applications. Full article

Background: Robotic-assisted thoracic surgery is increasingly recognized as an advanced minimally invasive technique for treating non-small cell lung cancer, offering technical advantages such as enhanced precision and visualization. Although numerous studies have been published worldwide, there are no comparable data from Poland. Therefore, evidence on the perioperative safety and oncologic adequacy of robotic-assisted lobectomy during early phase of program implementation within the Polish healthcare system remains limited. Methods: This retrospective, single-institution observational study included 81 consecutive patients who underwent robotic-assisted lobectomy for primary NSCLC between January 2022 and December 2024. All procedures were carried out using the da Vinci Xi system with a standardized four-arm portal approach. Clinical, perioperative, and pathologic parameters were prospectively collected and analyzed descriptively. Postoperative complications were classified according to Clavien-Dindo. Results: The median patient age was 70 years (IQR: 65–74), 52% were male, and 67% had a history of smoking. Adenocarcinoma was the predominant histologic subtype (51%). The median operative time was 176 min (IQR: 149–220). There were no conversions to thoracotomy and no 30-day mortalities. Postoperative complications occurred in 24% of cases, with prolonged air leak being most common (17%). The median hospital stay was 8 days (IQR: 6–10). R0 resection was achieved in 96% of patients, with a median of 14 lymph nodes dissected across 5 nodal stations. Conclusions: Robotic-assisted lobectomy performed during the early implementation phase of a national program demonstrated low morbidity, high rates of complete (R0) resection, and adequate lymph node yields consistent with international benchmarks. These results support the feasibility of robotic lobectomy within the Polish healthcare setting; however, the single-surgeon, single-center design limits generalizability. Further multicenter prospective studies are needed to confirm reproducibility, assess learning curves, and evaluate long-term oncologic outcomes. Full article

Robotic polishing in CAD-free industrial settings relies on point-cloud data, yet noise and non-uniform sampling often compromise kinematic feasibility and finishing quality. This paper proposes an adaptive motion planning approach with explicit kinematic constraints. A downsampling–clustering–mapping-back strategy is first employed for rapid workpiece extraction. Subsequently, an improved supervoxel representation and attributed adjacency graph (AAG) are developed, utilizing a multi-objective energy formulation to partition sub-regions that satisfy geometric consistency and kinematic reachability. To handle point-cloud noise, a lightweight neural network predicts scanning directions and step-distance coefficients, followed by thick-slice serpentine path generation. Finally, closed-loop verification ensures safety through inverse-kinematics and safety-margin checks. Experimental results demonstrate consistent sub-micron finishing quality, with Ra ≈ 0.6 μm on complex mold surfaces. Moreover, the proposed pipeline achieves a 7.5× preprocessing speedup, completing workpiece extraction in 1.14 s for a 237,640-point scan, and improves kinematic feasibility to 100% IK success while reducing the mean TCP normal deviation by ~76% compared with a PCA-based baseline. Full article

The rapid development of medical technologies requires architects to implement a future-proofing approach while designing medical facilities, despite the inherent uncertainty of long-term change. This challenge is particularly visible within hospital emergency departments (HEDs), which play a critical role as first-contact units and life-saving infrastructures. Due to their specific function, HEDs are a challenging environment for implementing new solutions, as they rely on proven frameworks designed to ensure continuity of care and operational efficiency. This raises the key question: how can modern technologies and architectural strategies streamline workflows in HEDs without overwhelming medical staff? Considering current challenges, an equally important factor in the development of emergency departments is their preparedness for crisis situations, such as pandemics, war threats and natural disasters. How can architectural design enable the implementation of given design strategies, aiming to ensure opportunities for development while simultaneously preparing for all-hazard scenarios? The authors gathered existing trends and solutions aimed at preparing hospital emergency departments for future challenges: positive/neutral, such as technological development, but also negative, such as currently ongoing war threats or risk of the next pandemic. Despite the apparent thematic extremity, certain systematic architectural solutions using a transdisciplinary approach may be the answer to these occurrences. The mentioned architectural solutions and factors were synthesized and subjected to design-oriented review based on existing case studies of a few Polish hospitals, which are simultaneously studied as case studies for broader doctoral research in the field of effectiveness assessment. The selected Polish hospital emergency departments are used as an illustrative, analytical reference to support the interpretation and synthesis of the reviewed literature. The contextual analysis enables the identification of transferable, design-oriented strategies relevant to broader emergence medicine architecture and applicable within European units. Examples from Polish units in particular are used as reference and background for discussion, rather than as empirical case studies. The study provides an overview of contemporary and future-oriented solutions in hospital architecture, focusing on the impact and feasibility within the hospital emergency departments. The synthesis highlights the importance of designing flexible spaces prepared for future technological advances, such as oversized service shafts, increased floor heights, and modular layouts. Additionally, the study focuses on the spatial connotations of emerging technologies like medical robotics, their maintenance areas and possible challenges. All of this is interrelated to social, demographic, and economic trends. These include the development of hospital networks, the evolving patient profile, inter-hospital information flow, and the growing role of highly specialized medical units. In terms of rapid challenges like wars or armed threats, factors revealed within the review indicate levels of HED readiness to face the conflict, mainly in terms of surge capacity but also structural durability and reserve resources. The post-pandemic context, in turn, assumes rapid expansion of the hospital into temporary and flexible structures and reversible zoning allowing for patient segregation and separation. Together, these insights outline pathways for creating resilient, adaptable, and efficient emergency care environments resilient to unforeseen challenges. Considering future scenarios of emergency departments, two main scenarios were identified: “the hospital of the future”, continuing overall development and adapting to rapid technological innovations, and “the crisis-resilient hospital”, resistant to various crisis scenarios, such as pandemics or war threats. The optimal development of the unit assumes both openness to technological changes and preparation of key zones for all-hazard scenarios. This review aims to synthesize architectural implications of technological and socio-demographic changes, not to provide a full empirical study. Adopting an exploratory framework, the review refers to technological innovations and crisis preparedness as external drivers shaping the spatial organization of hospital emergency departments and their adaptability to future challenges. Because of various inhibitors (economic, political, hierarchical), not all hospitals can introduce the described improvements, but the synthesis may serve as a knowledge source for future investments. The review was also conducted to support design decisions under conditions of uncertainty. The choice to address all the external factors collectively was induced to provide transferability of solutions and coherence of possible scenarios, which may happen simultaneously. Full article

Internal wall grinding of pipes constitutes a critical pretreatment procedure in the anti-corrosion repair operations of Prestressed Concrete Cylinder Pipes (PCCP). To address the limitations of low efficiency and poor safety associated with traditional manual internal wall grinding in PCCP anti-corrosion repair, this study presents the design of a support-wheel-type internal wall grinding robot for pipes. The robot’s structure comprises a walking support module and a grinding module: the walking module employs four sets of circumferentially equally spaced (90° apart) independent-support wheel groups. Through an active–passive collaborative adaptation mechanism regulated by pre-tensioned springs and lead screws, the robot can dynamically conform to the inner wall of the pipe, ensuring stable locomotion. The grinding module is connected to the walking module via a slewing bearing and is equipped with three roller-type steel brushes. During operation, the grinding module revolves around the pipe axis, while the roller brushes rotate simultaneously, generating a composite three-helix grinding trajectory. Mathematical models for the robot’s obstacle negotiation, bend traversal, and grinding motion were established, and multi-body dynamics simulations were conducted using ADAMS for verification. Additionally, a physical prototype was developed to perform basic functional tests. The results demonstrate that the robot’s motion characteristics are highly consistent with theoretical analyses, exhibiting stable and reliable operation, excellent pipe traversability, and robust driving capability, thus meeting the requirements for internal wall grinding of PCCP pipes. Full article

This study employs a multi-objective particle swarm optimization (MOPSO) algorithm to address the dual-objective challenge in the robotic polishing of Ti-6Al-4V. The aim is to determine optimal parameters that minimize surface roughness while maximizing the material removal rate (MRR), thereby improving both surface quality and processing efficiency. First, a material removal depth model for end-face polishing is established based on Preston’s equation and theoretical analysis, from which the MRR model is derived. Subsequently, orthogonal experiments are conducted to investigate the influence of process parameters and their interactions on surface roughness, followed by the development of a quadratic polynomial roughness prediction model. Analysis of variance (ANOVA) and model validation confirm the model’s reliability. Finally, the MOPSO algorithm is applied to obtain the Pareto optimal solution set, yielding the optimal parameter combination. Experimental results demonstrate that at a normal contact force of 7.58 N, a feed rate of 4.52 mm/s, and a spindle speed of 5851 rpm, the achieved MRR and Ra values are 0.2197 mm³/s and 0.291 μm, respectively. These results exhibit errors of only 5.64% and 2.65% compared to model predictions, validating the proposed method’s effectiveness. Full article

The removal of primer from aircraft skin epoxy resin primer plates was investigated by using an adaptive hydraulically controlled polishing tool in conjunction with an industrial robot. This study examined the effects of several key process parameters—grinding force, rotational speed, feed speed, and abrasive grit size—on primer removal depth and surface roughness. Through both single-factor analysis and response surface methodology (RSM), the variation patterns of removal depth and surface roughness with respect to these parameters were elucidated. RSM was employed to develop regression models for the primer removal depth and removal rate. The relative errors of these regression models were found to be within 8%, while the maximum relative error of the backpropagation neural network prediction model for surface roughness Ra is 9.5%. These models exhibit high accuracy in predicting the material removal depth, material removal depth rate, and surface roughness of the primer plates. The optimal parameters for the adaptive hydraulically controlled polishing tool were identified as flows: a polishing force of 20 N, a feed speed of 40 mm·s⁻¹, a rotational speed of 2000 rpm, and 80-grit sandpaper. Under these conditions, the maximum removal depth reaches 27.5 µm, the highest removal rate is 5.501 µm·s⁻¹, and the surface roughness Ra is 1.897 µm. Full article

This research tackles the intricate machining properties of cylindrical aspheric surfaces with a versatile adaption approach utilizing a robotic arm and a compact tool head, incorporating trajectory optimization. A three-step integrated error compensation framework was established as the core to address spatial inaccuracies in robotic systems, incorporating coordinate measuring machine (CMM)-based cylindrical generatrix offset correction, laser tracker-assisted progressive coordinate calibration, and contour profiler-driven feedback compensation. Complemented by a curvature-driven trajectory design, the method ensures uniform polishing coverage for non-uniform curvature surfaces. Experimental validation on S-TiH53 glass cylindrical aspheric components demonstrated a surface profile accuracy of peak-to-valley (PV) value ≤ 2 μm, meeting stringent requirements for high-power laser applications. This systematic approach enhances both efficiency and accuracy in robotic polishing, offering a viable solution for high-end optical manufacturing. Full article

In large optical mirror processing (LOMP), the robot is required to carry a computer-controlled optical surfacing (CCOS) polishing tool capable of both fully covering the required material removal profile and maintaining sufficient redundancy for process adaptability. The designed LOMP robot is a five-degree-of-freedom (5-DOF) hybrid robot, where the workspace of its parallel mechanism is constrained by dimensional parameters, including the moving platform radius, the fixed/moving platform radius ratio, and link lengths. This paper presents an optimization study of dimensional parameters for robotic systems, aimed at meeting the workspace requirements of 1250 mm-diameter large optical mirrors. First, analytical models of the robot’s effective workspace and driving torque under different dimensional parameters are derived. Subsequently, workspace requirements and driving torque are established as optimization constraints, and a differential evolution algorithm is implemented to determine the optimal dimensional parameters for the LOMP system. To improve computational efficiency, the conventional differential evolution algorithm is enhanced through the integration of adaptive mutation and crossover operators, resulting in a modified adaptive differential evolution algorithm (ADEA) that demonstrates accelerated convergence characteristics while maintaining solution accuracy. Finally, MATLAB simulations demonstrate that the proposed ADEA successfully obtains optimal dimensional parameter combinations while satisfying all specified constraints. Based on the optimal dimensional parameters, an engineering prototype was manufactured. Experimental results verified the accuracy of the optimized design, providing a valuable reference for optimization of dimensional and structural parameters in similar engineering equipment. Full article

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