Search Results (37)

The present work is aimed at developing and researching a robotic arm with five degrees of freedom, manufactured using 3D-printing technology and controlled by an ESP32 microcontroller. This technology is increasingly used in robotics, especially in the educational process, due to the possibilities for rapid prototyping, modification and restoration of individual components. In the development process, the mechanical, hardware and software parts of the system were implemented, and a basic kinematic analysis of the manipulator was performed. A control program was created, allowing the performance of “pick and place” tasks, as well as visualization and manual control through a developed application. The results obtained show that the developed system provides sufficient functionality and flexibility for use in robotics training, while at the same time allowing expansion and upgrading with additional functionalities. The main contribution of the work lies in the implementation of an accessible and adaptable robotic platform, suitable for educational and experimental purposes. Full article

Diffusion policies model multimodal robot action sequences, but behavioral cloning does not directly optimize task return. We present a structured scoping review of reinforcement learning for generative robot policies and a bounded state-based locomotion reproduction. Four documented routes yielded 178 records, 162 unique candidates, and an 84-study evidence map. Hierarchical rules distinguish 41 direct reward-driven studies from 32 adjacent robotic, eight alternative-generator, and three non-robotic studies; a five-axis taxonomy codes initialization/data, interaction regime, optimized object, credit assignment, and generator. Under a fixed-final evaluation protocol on the Datasets for Deep Data-Driven Reinforcement Learning (D4RL) 1.1 Hopper benchmark, five diffusion policy policy optimization (DPPO) fine-tuning seeds improved over their run-recorded behavior-cloning initializations by a mean of 1261.2 return, with a seed-level standard deviation of 125.5 and a 95% confidence interval of 1105.3–1417.1; the five runs link to two recorded behavior-cloning checkpoints. A Gaussian-policy control also improved after proximal policy optimization, so the gain was not diffusion-specific. A full-chain backpropagation adaptation exhibited clear seed-dependent variation, a matched action-divergence intervention did not establish causal critical timesteps, and reducing denoiser evaluations from 20 to 2 lowered A100 latency from 30.97 to 3.85 ms while substantially reducing normalized score. The experiments are limited to state-based locomotion and do not validate visual manipulation. Full article

To address the pervasive engineering challenges of rigid interference and subpar machining efficiency encountered during the complex freeform surface polishing of P20 mold steel, this study proposes and fabricates a structurally designed, five-petal composite compliant polishing tool via fused granulation fabrication (FGF). The tool structurally integrates a passive thermoplastic polyurethane (TPU) compliant buffer layer with an active PA66/diamond micro-cutting functional layer, achieving monolithic precision assembly through dual-temperature-zone 3D printing. Tensile mechanical characterization (n = 6) reveals that the composite interface attains an average ultimate tensile strength (UTS) of 59.39 ± 15.41 MPa (with a peak of 78.90 MPa) and an average elongation at break of 27.42 ± 7.41%, demonstrating exceptional structural robustness and fracture toughness under heavy-load abrasive machining conditions. During adaptive polishing validations on complex convex topographies and deep concave mold cavities, the compliant tool effectively compensated for normal vector spatial errors intrinsic to three-axis CNC machining via passive geometric adaptation. Topographical evaluations suggest a ductile-regime, differential asperity planarization material removal paradigm, which is attributed to the macroscopic 3D elastic deformation of the tool synergized with the proposed compliance of the polymer matrix. Following high-intensity sequential polishing regimens, the original macroscopic milling striations were substantially reduced. Quantitative profilometric analysis reveals that the average surface roughness of the convex profiles decreased from an initial 13.33 µm to 7.42 µm, while that of the restrictive deep concave features was reduced from 10.84 µm to 4.11 µm. Ultimately, this technological framework circumvents the traditional reliance on capital-intensive, six-degree-of-freedom robotic platforms, providing a scalable automated polishing protocol compatible with standard CNC systems for the cost-effective surface planarization of precision molds. Full article

To overcome the inherent limitations of conventional offline programming in adapting to dimensional deviations and assembly-induced errors during robotic welding of ship structures, this paper proposes a point-cloud-enhanced visual scanning paradigm that enables automatic weld seam identification and collision-free trajectory planning. A dedicated monochromatic vision system is rigidly integrated onto a six-axis industrial robot, enabling high-fidelity feature extraction and geometric contour reconstruction for the precise localization of multi-configuration weld seams. The proposed approach substantially reduces manual teaching operations, enhances environmental adaptability in unstructured shipbuilding workshops, and improves global positioning accuracy. The core technical contributions are threefold: (1) systematic design and precision calibration of the integrated robotic vision system, including a hand–eye calibration procedure; (2) development of a hybrid 2D image-3D point cloud processing pipeline that combines SURF and FLANN for image stitching with RANSAC-based plane segmentation and PCA-driven contour reconstruction; and (3) extensive experimental validation across five distinct workpiece configurations. These results confirm the system’s strong applicability for intelligent and efficient shipbuilding welding, significantly outperforming conventional offline programming, which exhibits deviations exceeding 5 mm under identical conditions. Quantitative error analysis demonstrates that the online recognition method achieves a weld localization root mean square error (RMSE)of 0.82 mm, a standard deviation of 0.45 mm, and a verified maximum absolute deviation of 1.5 mm. Full article

This article presents an integrated framework for robust control and cybersecurity of an industrial robot, combining Quantitative Feedback Theory (QFT), digital twin (DT) technology, and a programmable logic controller–based architecture aligned with the requirements of the NIS2 Directive. The study considers a five-axis industrial manipulator modeled as a set of decoupled linear single-input single-output systems subject to parametric uncertainty and external disturbances. For position control of each axis, closed-loop robust systems with QFT-based controllers and prefilters are designed, and the dynamic behavior of the system is evaluated using predefined key performance indicators (KPIs), including tracking errors in joint space and tool space, maximum error, root-mean-square error, and three-dimensional positional deviation. The proposed architecture executes robust control algorithms in the MATLAB/Simulink environment, while a programmable logic controller provides deterministic communication, time synchronization, and secure data exchange. The synchronized digital twin, implemented in the FANUC ROBOGUIDE environment, reproduces the robot’s kinematics and dynamics in real time, enabling realistic hardware-in-the-loop validation with a real programmable logic controller. This work represents one of the first architectures that simultaneously integrates robust control, real programmable logic controller-based execution, a synchronized digital twin, and NIS2-oriented mechanisms for observability and traceability. The conducted simulation and digital twin-based experimental studies under nominal and worst-case dynamic models, as well as scenarios with externally applied single-axis disturbances, demonstrate that the system maintains robustness and tracking accuracy within the prescribed performance criteria. In addition, the study analyzes how the proposed architecture supports the implementation of key NIS2 principles, including command traceability, disturbance resilience, access control, and capabilities for incident analysis and event traceability in robotic manufacturing systems. Full article

Natural and unconstrained locomotion remains a fundamental challenge in creating truly immersive virtual reality (VR) experiences. This paper presents the design and control of a novel robotic omnidirectional treadmill (ODT) based on the bilateral symmetry of two cooperative five-bar planar mechanisms designed to replicate realistic walking mechanics. The central contribution is a human in the loop control strategy designed to achieve stable walking in place. This framework employs a specific control strategy that actively repositions the footplates along a dynamically defined ‘Line of Movement’ (LoM), compensating for the user’s motion to ensure the midpoint between the feet remains stabilized and symmetrical at the platform’s geometric center. A comprehensive dynamic model of both the ODT and a coupled humanoid robot was developed to validate the system. Numerical simulations demonstrate robust performance across various gaits, including turning and catwalks, maintaining the user’s locomotion center with a maximum resultant drift error of 11.65 cm, a peak value that occurred momentarily during a turning motion and remained well within the ODT’s safe operational boundaries, with peak errors along any single axis remaining below 9 cm. The system operated with notable efficiency, requiring RMS torques below 22 Nm for the primary actuators. This work establishes a viable dynamic and control architecture for foot-tracking ODTs, paving the way for future enhancements such as haptic terrain feedback and elevation simulation. Full article

Inspired by the musculoskeletal structure of snakes, this study proposes a cable-driven continuum robotic system, comprising a dual-segment continuum arm and a linear feeding module. The continuum arm provides four joint degrees of freedom through coordinated cable actuation for snake-like bending, while the feeding module enables linear translation along the Z-axis, resulting in a total of five degrees of freedom. A constant-curvature kinematic model is developed, and a real-time inverse kinematics solution based on fifth-order Taylor expansion is proposed. To enhance postural stability, a master–slave teleoperation control framework is implemented that decouples translational motion from orientation control. Leveraging the geometric symmetry of its dual-segment design, the system achieves consistent end-effector orientation by coordinating bending angles and rotation directions between segments. Simulation and experimental results validate the accuracy of the kinematic model and demonstrate the robot’s capability for dexterous, stable movements in confined environments. The proposed continuum robot offers high positioning accuracy, structural adaptability, and strong potential for bioinspired applications in endoscopy and minimally invasive surgical procedures. Full article

Robust robot manipulation hinges on effective state estimation. The VRT 6 robot leverages an inertia measurement unit with triaxial gyroscopes, magnetometers, and accelerometers, as well as a position sensor, but these sensors are plagued by noise that demands rigorous filtering. To tackle this, an adaptively scaled unscented Kalman filter was employed. The filter’s scaling parameter was meticulously optimized using density- and moment-based techniques, as both system properties and estimated state impact this crucial parameter. A Maximum Likelihood Estimation (ML) substantiates the enhanced quality of the estimated velocity and acceleration, on par with the position estimate. Minimizing measurement prediction error (MMPE) also shows better results with less RMSE when compared to fixed-kappa values, and the quality of position estimates is higher with the increase in the domain of the scaling parameter. By carefully selecting the adaptive scaling parameters’ range to minimize sigma point weights and ensure the positive definiteness of the covariance matrix, this enhanced UKF method achieved markedly superior state estimates compared to standard UKF implementations. Full article

This study presents a fault-tolerant control system for Selective Compliance Assembly Robot Arm (SCARA) robots, ensuring operational continuity in cooperative tasks. It is evaluated in five scenarios: normal operation, failures without reconfiguration, and with active reconfiguration. The system employs redundant actuators, differential gears, torque limiters, and rapid detection and reconfiguration algorithms. Simulations in MATLAB R2024a demonstrated reconfiguration times of 0.5 s and reduced trajectory errors (0.0042 m on the X-axis for Robot 1), achieving efficiency above 99%. Nonlinear Model Predictive Controllers (NLMPCs) and Adaptive Sliding Mode Control (ASMC) were compared, with NLMPC excelling in stability and ASMC in precision. The system showcased high productivity in pick-and-place tasks, even under critical failures, establishing itself as a robust solution for industrial environments requiring high reliability and advanced automation. Full article

The present paper describes the measurement of the drift of unidirectional pose accuracy, repeatability, and static compliance of a collaborative robot employing a measurement methodology that relies on the description of a virtual ISO cube placed in the robot’s workspace. The measurements aimed to investigate and assess the suitability of the UR5 six-axis collaborative robot for its application in robotic 3D printing. An experimental laboratory measurement workstation was constructed to perform the measurements, and control measurements were performed. The measurements involved describing the TCP point of the robot tool at five measurement points located in a virtual ISO cube during a minimum of 30 repeated measurement cycles. A camera and six linear incremental sensors with assessment units were used for the measurements. The measurements were performed in compliance with the regulations of STN ISO 9283 standard for this type of measurement. As a result of the measurements, the technical specifications of the drift and static compliance of the controlled robotic arm were verified, and the results were compared with the values specified by the manufacturer. Following the measurements and assessment of the results, it was possible to assess the suitability of the used UR5 robotic arm for its application in robotic 3D printing and to propose possible recommendations for the calibration of the robot and the process settings of the printing system for the production of objects using FDM technology. Full article

This paper proposes a new algorithm for the automatic generation of toolpaths for machining complex geometric positions, such as molds used in orthosis production. The production of individualized orthoses often requires the use of multi-axis machining systems, such as five-axis machines or industrial robots. Typically, complex and expensive CAD/CAM systems are used to generate toolpaths for these machines, requiring the definition of a machining strategy for each surface. While this approach can achieve a reliable and high-quality machining process, it is very time-consuming and makes it challenging to meet the criteria for rapid production of orthopedic aids. Given that their production is a custom-made process using individual shapes as inputs, the toolpath generation process becomes even more demanding. To address these challenges, this paper proposes an algorithm suitable for the automatic generation of toolpaths for such complex positions. The proposed algorithm has been tested and has proven to be robust and applicable. Full article

Researchers have attempted to control robotic hands and prostheses through biosignals but could not match the human hand. Surface electromyography records electrical muscle activity using non-invasive electrodes and has been the primary method in most studies. While surface electromyography-based hand motion decoding shows promise, it has not yet met the requirements for reliable use. Combining different sensing modalities has been shown to improve hand gesture classification accuracy. This work introduces a multimodal bracelet that integrates a 24-channel force myography system with six commercial surface electromyography sensors, each containing a six-axis inertial measurement unit. The device’s functionality was tested by acquiring muscular activity with the proposed device from five participants performing five different gestures in a random order. A random forest model was then used to classify the performed gestures from the acquired signal. The results confirmed the device’s functionality, making it suitable to study sensor fusion for intent detection in future studies. The results showed that combining all modalities yielded the highest classification accuracies across all participants, reaching $92.3\pm 2.6\%$ on average, effectively reducing misclassifications by 37% and 22% compared to using surface electromyography and force myography individually as input signals, respectively. This demonstrates the potential benefits of sensor fusion for more robust and accurate hand gesture classification and paves the way for advanced control of robotic and prosthetic hands. Full article

Background: POP (pelvic organ prolapse) involves the descent of one or more pelvic organs downwards with or without protrusion from the vaginal opening, caused by the relaxation and weakening of ligaments, connective tissue, and pelvic muscles. Such an outcome negatively impacts the quality of life. The gold standard procedure for repairing apical compartment prolapse is colposacropexy (CS) to secure the anterior and posterior walls of the vagina to the anterior longitudinal sacral ligament, located anteriorly to the sacral promontory, using a mesh. Several surgical approaches are feasible. Laparotomic or minimally invasive methods, including laparoscopic or robotic ones, can restore the horizontal axis of the vagina and typically involve concomitant hysterectomy. Methods: This study is based on 80 patients who underwent CS at Palermo’s Ospedali Riuniti Villa Sofia-Cervello from 2019 to 2023. Women aged 35–85 at the time of surgery were divided into two groups: 40 patients underwent mini-laparoscopic surgery, and 40 patients underwent robotic surgery. The following parameters were accounted for: demographic data (initials of name and surname, age), preoperative clinical diagnosis, date of surgery, surgical procedure performed, estimated intraoperative blood loss, duration of surgical intervention, length of hospital stay, postoperative pain assessed at 24 h using the VAS scale, and any complications occurring in the postoperative period. Mini-laparoscopic CS (Minilap) and robotic CS (Rob) were then compared in terms of outcomes. Results: In the Minilap group, 11 patients out of 40 had a preoperative diagnosis of vaginal vault prolapse. The average age in this group was 61.6. Five of these patients had isolated cystocele, while the rest presented vaginal stump prolapse linked to cystocele, rectocele, or both. The remaining 29 patients in the Minilap group had a preoperative diagnosis of uterovaginal prolapse, also associated with cystocele, rectocele, or both, or isolated in nine cases. In the Rob group (average age: 60.1), 13 patients were diagnosed with vaginal prolapse (isolated or associated with cystocele), while the remaining 27 had a diagnosis of uterovaginal prolapse. In the Minilap group, the average procedure duration was 123.3 min, shorter than the Rob group (160.1 min). Conclusions: The data collected throughout this prospective study point to the mini-laparoscopic approach as being preferable over the robotic one in terms of surgical procedure length, intraoperative blood loss, postoperative pain, and aesthetic outcome. Hospital stay duration and post operative complication rates were similar for both groups. The innovative and ever-progressing nature of such procedures calls for novel standards prioritizing patient care as well as medicolegal viability. Full article

Total knee arthroplasty (TKA) is a well-established and successful treatment option for patients with end-stage osteoarthritis of the knee, providing high patient satisfaction. Robotic systems have been widely adopted to perform TKA in orthopaedic centres. The exact spatial positions of the femur and tibia are usually determined through pinned trackers, providing the surgeon with an exact illustration of the axis of the lower limb. The drilling of holes required for mounting the trackers creates weak spots, causing adverse events such as bone fracture. In the presented computational feasibility study, time differential electrical impedance tomography is used to locate the femur positions, thereby the difference in conductivity distribution between two distinct states $s_0$ and $s_1$ of the measured object is reconstructed. The overall approach was tested by simulating five different configurations of thigh shape and considered tissue conductivity distributions. For the cylinder models used for verification and reference, the reconstructed position deviated by about $\approx 1$ mm from the actual bone centre. In case of models mimicking a realistic cross section of the femur position deviated between 7.9 mm 24.8 mm. For all models, the bone axis was off by about $\phi =1.50°$ from its actual position. Full article

In a global context, where the construction industry is a major source of CO₂ emissions and resource use, is dependent on concrete and its risks, and lags behind in digitalization, a clear need arises to direct architecture towards more practical, efficient, and sustainable practices. This research introduces an alternative technique for building timber space structures, aiming to expand its applications in areas with limited access to advanced technologies such as CNCs with more than five axes and industrial robotic arms. This involves reconfiguring economic and ecological constraints to maximize the structural and architectural advantages of these systems. The method develops a parametric tool that integrates computational design and manufacturing based on two-axis laser cutting for shells with segmented hexagonal plywood plates. It uses a modified ‘half-lap joint’ mechanical joint, also made of plywood and without additional fasteners, ensuring a precise and robust connection. The results demonstrate the compatibility of the geometry with two-axis CNC machines, which simplifies manufacturing and reduces the cuts required, thus increasing economic efficiency. The prototype, with a span of 1.5 m and composed of 63 plywood panels and 163 connectors, each 6 mm thick, supported a point load of 0.8 kN with a maximum displacement of 5 mm, weighing 15.1 kg. Assembly and disassembly, carried out by two students, took 5 h and 1.45 h, respectively, highlighting the practicality and accessibility of the method. In conclusion, the technique for building timber shells based on two-axis CNC is feasible and effective, proven by practical experimentation and finite element analysis. Full article