Search Results (17)

The positional repeatability of industrial robots is a critical yet state-dependent performance metric, highly sensitive to thermal conditioning and mechanical loading. This study develops a data-driven framework for predicting repeatability of FANUC LR Mate 200iD (FANUC, Oshino-mura, Japan) and KUKA KR 6 R700 Sixx (KUKA AG, Augsburg, Germany) robots under varying operational conditions. ISO 9283-compliant experiments using a TriCal system (TRI-CAL Ltd., Montreal, QC, Canada) were conducted across three warm-up durations, three payload levels, and five poses. Ensemble artificial neural networks with 10 independently trained networks were developed for each robot. The FANUC model achieved R² = 0.9922, RMSE = 0.004231 mm, and MAE = 0.002979 mm, while the KUKA model achieved R² = 0.9926, RMSE = 0.002919 mm, and MAE = 0.002215 mm. Prediction interval coverage was 93.3% for FANUC and 100% for KUKA. Per-pose R² ranged from 0.9588 to 0.9966 for KUKA. Response surface analysis identified thermal stabilization as the dominant factor affecting repeatability, with improvements of 86% for FANUC and 84% for KUKA after 4 h of warm-up. The KUKA robot demonstrated superior robustness and lower variability compared to the FANUC robot. The framework provides a practical tool for predicting repeatability, supporting process planning, uncertainty budgeting, and precision manufacturing optimization. Full article

With contemporary advancements in additive manufacturing (AM), it has become possible to obtain hull structures for spacecraft made of relatively cheap materials. The possibility of substituting super-austenitic stainless steel Avesta SMO 254 X1NiCrMoCuN20-18-7 (EN 10088) for that already used in the Starship SpaceX 304 L-Modified is focused on achieving better thermal stability and durability in extreme conditions. The Directed Energy Deposition Arc (DED-Arc) method for AM has enabled the production of high-strength-to-weight ratios. The aim is to engage low-cost material with treatment optimization to provide greater corrosion resistance and high yield and tensile strength. For the DED-Arc, a filler wire was selected for the welding source, Fronius TPS 400i. A simulation via the RoboDK Robot Development Kit for the FANUC ARC Mate 100ID10L is provided. Additional shot pining/vibration treatment is proposed for the finished structure, which can be a substitute for the cold-worked initial metal. A comparison is made for stainless steel that has already been tested for space travel. Regimes for the manufacturing process are proposed, with representative samples of Avesta SMO 254 obtained and tested using microhardness measurements, microcracking detection, porosity measurements, interface zone assessment, and microstructural analysis. The DED-Arc process can be applied to large-space shell manufacturing. A comparison is made with a focus on the mechanical and corrosion advantages. For Avesta SMO 254, microhardness measurements ranged from 235 to 246 HV1 and increased after treatment. The controlled parameters provided a maximum heat input of 0.7 KJ/mm, no defects, and a fine microstructure. The successful use of stainless steel with AM increases the potential for multiple space missions. The advanced method shows high quality, allows cost savings and provides extended service life. Full article

This study analyzed the effect of forming temperature on the roller hemming process of AA6011-T4 aluminum alloy sheets, using a 2^K factorial design to also evaluate the influence of roller diameter and flange height. A total of 24 experimental tests were conducted, varying the forming temperature (23 °C and 50 °C), roller diameter (22 mm and 50 mm), and flange height (7 mm and 10 mm). The hemming process was performed using a six-axis industrial robot (FANUC 2000i, Fanuc Corporation, Oshino, Japan) with roller tooling mounted o n a support fixture. The height of the flanged profile was measured using a coordinate measuring machine. ANOVA results, processed with MINITAB 18, showed that forming temperature, roller diameter, and flange height all have a statistically significant effect on the final profile height. No significant interactions were found among the factors, indicating their effects are independent. The most favorable configuration for maximizing profile height was the combination of the largest roller diameter and the highest flange height, under cold forming conditions. Additionally, a significant difference was observed between cold and warm forming processes in terms of the resulting profile height, highlighting the relevance of temperature control in the roller hemming of AA6011-T4 aluminum alloy. Full article

The rapid development of digital manufacturing and robotic systems places increased demands on the accuracy and reliability of industrial manipulators. Traditional time-based reliability metrics do not reflect the robot’s ability to consistently achieve the desired position and orientation within process tolerances or the probability of the end-effector falling into a given area of permissible poses. The proposed framework integrates a deterministic kinematic model, a stochastic representation of Denavit–Hartenberg parameters and control variables, analytical methods for estimating probabilities, and numerical modeling using the Monte Carlo method. The methodology has been tested on the widely used industrial robot FANUC LR Mate 200iD/7L. The results demonstrate a significant dependence of geometric reliability on the kinematic configuration of the manipulator, with maximum reliability in compact poses and a significant reduction in elongated configurations near singularities. Comprehensive validation was carried out, including numerical experiments on a planar prototype, high-precision physical measurements on a real robot and analysis of operational data, which confirmed the adequacy of the proposed model. The developed approach provides a powerful tool for designing, optimizing and predicting the reliability of robotic cells in high-precision automation environments. 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

To address the problems of low success rate, excessively long obstacle avoidance paths, and a large number of invalid nodes in path planning for robotic arms in complex environments, this paper proposes an obstacle avoidance path planning method based on the Cauchy Chaotic African Vulture Optimization Algorithm (CC-AVOA). By introducing a Cauchy perturbation term, the algorithm retains a certain degree of randomness in the later stages of the search, which helps to escape local optima. Furthermore, the introduction of a logical chaotic mapping increases the diversity of the initial vulture population, thereby improving the overall search efficiency of the algorithm. This paper compares the performance of the CC-AVOA algorithm with the standard African Vulture Optimization Algorithm (AVOA), the Rapid Exploratory Random Tree (RRT) algorithm, and the A* algorithm through simulation experiments in MATLAB R2024a under two-dimensional, three-dimensional, and robotic arm space environments. The results show that the CC-AVOA algorithm can generate paths with fewer nodes and shorter paths. Finally, the CC-AVOA algorithm is validated on both the RoboGuide industrial simulation platform and a physical FANUC robotic arm. The planned trajectories can be accurately executed without collisions, further confirming the feasibility and reliability of the proposed method in real industrial scenarios. Full article

Robotization of production processes and the use of 3D vision systems are currently becoming more and more popular. It allows for more flexibility in the robotic process as well as expands the possibilities of process control, depending on changes in the parameters of the object, its pose, and changes in the process itself. Unfortunately, the use of standard solutions is limited to a relatively small space in which the robot’s vision system operates. The use of the latest solutions in the field of Artificial Intelligence (AI) and external vision systems, in combination with the closed structures of industrial robot control systems, provides advantages by enhancing the digital awareness of the environment of robotic systems. This article presents an example of solving the problem of low digital awareness of the environment of robotic systems resulting from the limited field of view of vision systems used in industrial robots, while maintaining high precision of the systems consisting of the combination of a 3D vision system using a stereovision camera and software with AI elements with the control system of an industrial robot from FANUC and an integrated Robot Vision (iRVision) system to maintain the positioning accuracy of the robot tool. Full article

Autonomous robotic manipulators in industrial environments face significant challenges, including time-varying payloads, multi-source disturbances, and real-time computational constraints. Traditional model predictive control frameworks degrade by over 40% under model uncertainties, while conventional adaptive techniques exhibit convergence times incompatible with industrial cycles. This work presents a hybrid adaptive model predictive control framework integrating edge artificial intelligence with dual-stage parameter estimation for 6-DoF industrial manipulators. The approach combines recursive least squares with a resource-optimized neural network (three layers, 32 neurons, <500 KB memory) designed for industrial edge deployment. The system employs innovation-based adaptive forgetting factors, providing exponential convergence with mathematically proven Lyapunov-based stability guarantees. Simulation validation using the Fanuc CR-7iA/L manipulator demonstrates superior performance across demanding scenarios, including precision laser cutting and obstacle avoidance. Results show 52% trajectory tracking RMSE reduction (0.022 m to 0.012 m) under 20% payload variations compared to standard MPC, while achieving sub-5 ms edge inference latency with 99.2% reliability. The hybrid estimator achieves 65% faster parameter convergence than classical RLS, with 18% energy efficiency improvement. Statistical significance is confirmed through ANOVA (F = 24.7, p < 0.001) with large effect sizes (Cohen’s d > 1.2). This performance surpasses recent adaptive control methods while maintaining proven stability guarantees. Hardware validation under realistic industrial conditions remains necessary to confirm practical applicability. Full article

Problem: Existing Human–Robot Collaboration (HRC) allocators cannot react at a sub-second scale while accounting for worker fatigue. Objective: We designed a fatigue-aware combinatorial auction executed every 100 ms. Method: A human and a FANUC robot submit bids combining execution time, predicted energy, and real-time fatigue; a greedy algorithm (≤1 ms) with a $1-1/e$ approximation guarantee and O (|Bids| log |Bids|) complexity maximizes utility. Results: In 1000 RoboDK episodes, the framework increases active cycles·min⁻¹ by 20%, improves robot utilization by +10.2 percentage points, reduces per cycle fatigue by 4%, and raises the collision-free rate to 99.85% versus a static baseline (p < 0.001). Contribution: We provide the first transparent, sub-second, fatigue-aware allocation mechanism for Industry 5.0, with quantified privacy safeguards and a roadmap for physical deployment. Unlike prior auction-based or reinforcement learning approaches, our model uniquely integrates a sub-second ergonomic adaptation with a mathematically interpretable utility structure, ensuring both human-centered responsiveness and system-level transparency. Full article

This article presents the results of applied research focused on the development of a hybrid software solution, which is based on the ABB RobotStudio 2021 suite, because even in the latest version, RobotStudio 10 does not have a dedicated virtual commissioning module. The aim of the study is to explore the potential communication capabilities between ABB RobotStudio and Siemens Simatic Robot Integrator and to unify control systems for performing virtual commissioning tasks. The proposed solution offers valuable procedures for any end user responsible for implementing robotic cell virtual commissioning tasks and ensures the compatibility between hardware and software components from ABB and Siemens manufacturers integrated into any robotic cell type. Siemens, one of the leading PLC manufacturers, offers the complex PLM platform Process Simulate, which can be integrated with the Totally Integrated Automation (TIA) Portal and Mechatronics Concept Designer (MCD) for developing virtual commissioning (VC) applications. The TIA Portal is recognized by robotics application integrators as the most efficient work environment for VC. However, there is currently no direct compatibility between the ABB RobotStudio (RS) platform and Siemens TIA Portal. To address integration challenges, Siemens has introduced the Simatic Robot Integrator (SRI) platform, which ensures compatibility with certain proprietary software from various robot manufacturers, including KUKA, Motoman, and Staubli. While Siemens has collaborated with manufacturers like KUKA and Kawasaki, major industry manufacturers such as ABB and Fanuc have yet to establish a standardized interface within the Siemens SRI platform. A mathematical model was also developed, which serves as a key perspective and a valuable tool for the future integration of double-portal-type robots into the working environments of ABB and Siemens. This integration aims to facilitate virtual commissioning in scenarios where such robots need to be implemented. Currently, ABB’s library does not include double-portal-type robots, despite the fact that leading manufacturers of double-portal robot types utilize ABB’s IRC5 controllers. Full article

Descriptions of the main CARC environments for programming industrial robots are given, describing the main used programming environments for various robot manufacturers such as ROBOGUIDE developed by FANUC Robotics, KUKA Sim and Kuka Work Visual developed by KUKA ROBOTICS, Robot Studio developed by ABB Robotics, K-ROSET and K-ROSET LITE developed by Kawasaki Robotics, Visual Component, DELMIA ROBOTICS of Dassault Systems, Tecnomatix Robotics & Automation Simulation of SIEMENS PLM Software/Simatic Robot Integrator, Visual Components, etc. A methodology describing the main stages, when working with computer systems, of off-line programming of industrial robots is proposed. The features characterizing the implementation of the stages defined in the methodology have been specified. The created methodology has been applied when working with the Fanuc ROBOGUIDE computer system. When using the given example of the Fanuc ROBOGUIDE, the emphasis is also on expanding the working space of the robot (Robot Envelope) by adding a 7th axis. The general software options that are added when performing this task are described, and two sample programs are given for the implementation of the given example—and a 3D simulation is made for moving a part (box). A control program has been generated for an industrial robot Fanuc LR Mate 200 iD/7L that shall perform “Pick and Place” operations and shall service a conveyor for the transportation of cartons and their arrangement on pallets. Full article

Because they are safe and easy to use, collaborative robots are revolutionizing many sectors, including industry, medicine, and agriculture. Controlling their dynamics, movements, and postures are key points in this evolution. Inverse kinematics is then crucial for robot motion planning. In 6R serial robots, achieving a desired pose is possible with different joint combinations. In this paper, our focus lies in studying forward and, mainly, inverse kinematics of the FANUC CRX-10iA cobot, a 6R cobotic arm with a non-spherical wrist. Its specific structural parameters implies that no analytical solutions exist except for some particular situations. FANUC does not provide the complete set of inverse kinematic solutions, even when 16 solutions are possible, only 8 of them are provided in Roboguide software. Furthermore, the existing literature on joints-to-workspace mapping for CRX cobots is currently very limited. It either lacks or provides partial or inconsistent inverse kinematics analysis. We present and detail a novel fully geometric method for numerically solving inverse kinematics meeting the requirement of high precision and a fast response. This approach provides both the exact number of inverse kinematics solutions and the sets of joint angles even for singular configuration. Its effectiveness was verified through simulations using the Roboguide Software and experimentation on the actual CRX-10iA cobot. Several examples (8, 12, or 16 inverse kinematic solutions) have enabled us to validate and prove the robustness and reliability of this geometric approach. Full article

This paper addresses the phenomenon of sloshing and the issues that arise during liquid handling at visual inspection stations. The pharmaceutical industry, recently put under pressure by the pandemic, has long adopted modular solutions consisting mainly of robotic islands. This work focuses on a visual inspection island for glass vials and ampules called VRU. This machine uses robotic arms to optimize the inspection process and enables automated control of a wide range of products using image recognition techniques and AI algorithms. However, the handling of containers in the presence of liquids requires special precautions to avoid the occurrence of bubbles inside the fluid that can prevent the cameras from correctly capturing any defects present. The banal solution involves a drastic reduction in the speeds and accelerations to which the liquids are subjected. However, using appropriate techniques makes it possible to achieve performance values similar to those obtainable when manipulating solid materials. The developed algorithms were tested using multibody simulations in the Mathworks Simscape environment and then validated using a six-axis Fanuc robot. In this study, however, the analysis conducted aimed to determine the correlations between trajectories, laws of motion, and sloshing in containers handled at high speed in industrial applications. In this study a multibody model was developed using a CFD analysis. The container consisted of a glass vial for pharmaceutical uses containing a liquid inside. The results obtained from the CFD analysis allowed us to calibrate the multibody model for the next phase of optimization of the laws of motion to be followed by the manipulator. Full article

In the field of robotic automation, achieving high position accuracy in robotic vision systems (RVSs) is a pivotal challenge that directly impacts the efficiency and effectiveness of industrial applications. This study introduces a comprehensive modeling approach that integrates kinematic and joint compliance factors to significantly enhance the position accuracy of a system. In the first place, we develop a unified kinematic model that effectively reduces the complexity and error accumulation associated with the calibration of robotic systems. At the heart of our approach is the formulation of a joint compliance model that meticulously accounts for the intricacies of the joint connector, the external load, and the self-weight of robotic links. By employing a novel 3D rotary laser sensor for precise error measurement and model calibration, our method offers a streamlined and efficient solution for the accurate integration of vision systems into robotic operations. The efficacy of our proposed models is validated through experiments conducted on a FANUC LR Mate 200iD robot, showcasing notable improvements in the position accuracy of robotic vision system. Our findings contribute a framework for the calibration and error compensation of RVS, holding significant potential for advancements in automated tasks requiring high precision. Full article

This study examines the practicality and limitations of using a FANUC CRX-10 iA/l collaborative robot to assemble a product component, highlighting the trade-offs between increased robotization and reduced manual intervention. Through a detailed case study in the i-Labs laboratory, critical factors affecting precision assembly such as station layout, tooling design and robot programming are discussed. The findings highlight the benefits of robots for nonstop operation, freeing up human operators for higher value tasks despite longer cycle times. In addition, the paper advocates further research into reliable gripping of small components, a current challenge for robotics. The work contributes to open science by sharing partial results and methods that could inform future problem solving in robotic assembly. Full article